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2023/08/15
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<issue_start>username_0: I am currently looking for a PhD program in Aerospace Engineering and I am going to ask by email if my research interest and thesis work fits the university research areas. Hence, I thought to summarize my thesis and produce a two-page-long document in the form of paper by using one of the following Overleaf templates: <https://www.overleaf.com/latex/templates/springer-nature-latex-template/myxmhdsbzkyd>, <https://www.overleaf.com/latex/templates/springer-conference-proceedings-template-updated-2022-01-12/wcvbtmwtykqj>. Instead of simply attaching the abstract of my thesis, I would like to provide an in-depth look at my work and hopefully show my passion and interest in the topic of the thesis.
Do you think this is a good idea? If so, which of the two templates do you suggest using?
P.s. Please feel free to suggest other Overleaf template
P.p.s. my thesis work was presented at an ESA ESTEC conference by my supervisor in the form of a two-pages abstract that was published (<https://indico.cern.ch/event/1158038/>). She told me I could write my own instead of using it to avoid plagiarism.<issue_comment>username_1: >
> Do you think this is a good idea?
>
>
>
I don't think anyone is going to spend the time reading 2 pages about your work to help you decide whether or not you should apply to graduate school at that institution: it's your job to figure out where to apply.
I don't think the Overleaf template will change that one way or the other, and be careful about pretending to make your work more official than it is, like making it appear to be a published manuscript when it isn't - this is usually quite apparent and could make people uncomfortable even if you don't intend to mislead. Cranks seem to do this sort of thing often.
Get used to summarizing your work in a *much* shorter format, be comfortable with a 2-minute summary of your work that you can do without any supporting material ("elevator speech").
If your MS thesis work is publishable but isn't published, I'd work on getting it published and post a preprint in the meantime; your masters' thesis advisor(s) can hopefully help you with that step.
>
> She told me I could write my own instead of using it to avoid plagiarism.
>
>
>
This sounds totally backwards to me. If it's your work, you should be an author on the submission whether or not you presented it and if you are an author then that work is yours, no need to write a new version: a work you coauthor is your work. If, on the other hand, you write a new version, it's likely that this new version will be seen as plagiarizing your supervisors previous work! Even if you cite properly, it could be seen as trying to game publication counts by getting credit for the same project twice.
Upvotes: 4 <issue_comment>username_2: If you really want to contact people like this, I recommend writing a 3-4 sentence summary, max. In general, though, I don't appreciate emails of this nature that are clearly mass-mailed, especially when after reading two sentences it's clear that a student's work has nothing to do with anything that I do.
"Does my work fit your research area?" is a question that shouldn't be necessary to ask. A simple search for a faculty member's body of work should be more than enough to answer the question on your own. Then, you could write emails that say "I work in your area, and here's why I think I might be a valuable asset to your research". When you include a 3-4 sentence summary of what you consider your area to be, you show good communication skills, which is probably more important from a recruiting aspect than what your master's work was.
Upvotes: 3 [selected_answer]
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2023/08/15
| 1,619
| 6,728
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<issue_start>username_0: I have been on the postdoc treadmill for 5 years now. My current employer has been clear from the start that unless I meet certain metrics with publications, I would not be able to stay past my current contract, which expires this year.
An ex-co-author of mine, who works at another institution, recently won a grant for a five year research project that is right on my field of expertise. She has struggled to recruit a candidate that meets the job requirements and on the second round of advertisement for a postdoc position, she encouraged me to apply for the job. My current employer strongly supported my application for this position. When I received an offer to join as a postdoc on the 5 year project of my colleague, my current employer made a surprise offer, for a 5 year contract extension and with an immediate 24% salary increase (despite still not meeting the publication requirements mentioned by my employer).
I have known my co-author for ten years. She was my undergraduate and graduate teacher and advised me heavily during my PhD. We have worked together in other research projects. I brought up the surprise offer from my current employer and she said that I should pick the offer that is best for my career and family. However, she also said that if she failed to hire a postdoc, that she would run into problems with the organization funding the project.
I am torn. I dont know how to tell my colleague that I will be declining the postdoc offer. I dont even know if I should decline it. The project I am currently working on is great and I have a good relationship with my research team. The PI is relatively younger and less well known than my colleague offering me a postdoc. The project that my colleague will be working on is also right on my field of expertise. So both projects are interesting, last about the same time but have a very large difference in terms of salary. The postdoc at my colleague's institution would also require me to move to another state.
What should I do? Do you have any advice?<issue_comment>username_1: She has already indicated that it is your choice and you should choose to your own benefit. She has other options for a postdoc and it is her responsibility, not yours, to fill the slot.
Just say that your other offer is better and that you will accept it. She may be disappointed, but it would be no reason to cut you off for future contact/collaboration.
Some things just need to be said. Better in person if you can manage it and don't make it sound like you are fishing for a better offer, though that is a possibility, perhaps. Talk to her before you finalize anything.
Upvotes: 5 <issue_comment>username_2: >
> she said that I should pick the offer that is best for my career and family
>
>
>
This advice is as good as any other you'll get. There is more to "career" than just salary, of course, but you shouldn't ignore it, either.
Do consider that you'll need a new job in 5 years that may or may not be in academia. But, there's no real way for an outsider to make the decision for you: you'll have to weigh all aspects of the decision and make a choice based on your own values.
Upvotes: 4 <issue_comment>username_3: I suggest first **signing the contract** with the position you want, or at least getting a written offer and making sure it matches your expectations, then declining the other offer.
In the meantime you can tell both PIs that you are considering their offers.
The fact that your colleague might have problems if they don't find a postdoc is not *your* problem, even if you like them. What you could do to help is say you'll help advertise the job description to your network.
Upvotes: 3 <issue_comment>username_4: It's your life and your decision, and it also seems that you already made your choice with the title asking *how to reject* the offer, not if you should accept the offer or not. There's no subtle way to throw a grenade, so if that's your decision, just say that.
HOWEVER. If you have not yet made a decision, let me offer a suggestion. Your ex-co-author saying that you should choose the best for your career does not mean that the other option is better. Three reasons: (1) Your ex-co-author is an upfront person, told you about the opportunity and selected you without any BS. Your current employer only removed conditions and gave you an offer after they saw you had another offer. I prefer people who don't need to have their arms twisted to do the right thing. (2) Instead of using manipulating language, give you false promises, or guilt you into accepting, your ex-co-author asked you to do what's best for you. Your current employer is only offering more money, not showing any other concern for you. (3) You have known her for 10 years, and she needs you to keep her grant. She seems the type of person who will have your back when you need it, and by accepting her offer, you will have shown that you had her back when she needed you. Your current employer seems transactional.
I always prefer a bigger salary to a smaller salary, but an honest, straight-forward, known quantity is in my book, worth the 25% salary difference.
Upvotes: 6 [selected_answer]<issue_comment>username_5: A post doc is a financial transaction: your time for their money. Treat it as such.
No one is doing anyone a favor here. Pick the best salary/most advantageous position for YOU. The rest is the problem of the PI. I am sure that if they really needed someone, they will offer more money and find it.
Upvotes: 2 <issue_comment>username_6: A post-doc is not a way of life. A string of 5-yr postdocs is not a career. If this were your last post-doc, which would you choose? I would look at it that way.
The post-doc is a low-paying holding pattern for people reluctant to leave academia but not successful enough to get a faculty position. Consider this to be your last post-doc. Then which one would you take? Even if it's not your last post-doc, two 5-year post-docs is no way to live, and it probably SHOULD be your last post-doc.
Academia is a pyramid scheme. Some people finish their PhDs in an area that suddenly becomes stone-cold. Some people finish their PhDs during a recession when big lights in the field are clamoring to go back to academic positions. Just because your timing was not good, is not necessarily your fault. I finished my PhD and got an immediate faculty offer at a highly rated school, but it was the lowest paying institution in north america (relative to the cost of living). I stayed as a faculty member for only 2 years.
That light at the end of the tunnel - even if it appears - may be exceedingly dim. Life is that way. Not every dream comes true.
Upvotes: 0
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2023/08/15
| 479
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<issue_start>username_0: Say you have just finished your PhD or you are a young post-doc researcher. You are applying for a faculty position at a university which is far from your hometown and far from where you currently live. After some years you will get your tenure-track. How would you respond to the following questions?
1. Why have you chose that university instead of a university close your hometown or to the place where you currently live? Say there is no big difference between both, except for their location.
2. How can you ensure that you will keep the same level of productivity in terms of research after you become a professor?
3. How would you deal with conflicts with people from other departments (for example, professors from other departments are deliberately sabotaging you and your students)?
4. How would you cope with adversities related to a professor career (low salary, lack of students to do research, busy solving tasks not related to teaching or research, etc)?
5. Wouldn't you prefer to be a professor at a low level university for a much higher salary but with no possibility of tenure-track? Why not?<issue_comment>username_1: 1. Because you have an open position in my field, whereas my local university does not.
2. I cannot, but then nobody can. Life happens.
3. Is this a situation common in your university? If yes I withdraw my application. If no I’ll deal with this if I ever have to.
4. If I accept the position, I accept the salary on offer and the other conditions of the job as well.
5. If I am offered such a position at the same time as I have your offer, I will evaluate both offers for what they are and choose in my best interest.
Upvotes: 1 <issue_comment>username_2: I know it's a radical notion, but I would respond with the truth.
What the truth is for you is not the same as it is for me, or anyone else who responds. They are all opinions and personal questions.
Except #2. No one can guarantee that.
Upvotes: 2
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2023/08/16
| 805
| 3,596
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<issue_start>username_0: In 2021, PRX Quantum released a new type of publication distinct from articles and reviews known as the tutorial. This is described as:
>
> PRX Quantum began publishing Tutorials to help the quantum community educate the next generation of quantum scientists. Rather than provide a comprehensive overview of the field, as is typically found in a Review paper, Tutorials are hands-on guides written by experts invited by the editorial leadership of the journal. Tutorials focus on the essential knowledge and relevant references that will allow newcomers to a research field, approach, or methodology efficiently move forward with their work. For example, they should ideally help researchers migrate to a new field, bridge knowledge gaps for interdisciplinary collaborators, and contribute to the education and development of PhD students and postdocs. They focus on explaining well-established milestone concepts, the latest techniques, and developments in the field, providing a flavor of current research.
>
>
>
I've noticed these hand hold the reader very closely and are in its own distinct category from review articles as mentioned in the quote. Where can I find a repository of other such journals and what exactly am I looking for in terms of search words when it comes to this looking for journals that will publish this type of article? Also, do the somewhat more vanilla journals such as "PRB" or "EJP" accept these kinds of tutorial articles?<issue_comment>username_1: It feels to me like this recent PRX Quantum approach is fairly novel, and I'm fairly jealous that I haven't seen anything like that in areas that I'm responsible for teaching.
If I were looking for resources like this, there are a number of approaches I would try. Since the publication class you're describing looks like just another type of publication in a journal, I would try to search for people who have cited publications of this type, and hope to hit some article on education that compares the efficacy of works of this type to more traditional methods. If such papers exist, they may well point you to other similar resources.
A second approach would be to try to find journals that specialize in education in the areas you're interested in. This, of course, would cast a wider net than what you're looking for, but the advantage is that you may find a bigger picture that brings you even more tools. As an example of such a journal, I'll point you to [Advances in Physiology Education](https://journals.physiology.org/journal/advances)
Lastly, a chat with a good university librarian when you're looking for resources is never a bad idea.
Good Luck! If you do find such resources, it would be fantastic if you can post them as an answer to your own question!
Upvotes: 3 [selected_answer]<issue_comment>username_2: One way journals compete is by offering different content types and filling different niches. Tutorials is a fairly unique type that, as far as I know, is only offered by two APS journals: PRX Quantum and PRX Energy. Traditionally in physics, guides and hands-on material have commonly been written up as lecture notes. Especially summer school lecture notes can have a similar nature. A fairly recent avenue that may be of interest is the journal SciPost Physics Lecture Notes. Otherwise, lecture notes have often ended up being published in various forms, including book volumes, review articles, or just PDFs. Finally, as username_1 writes, some pedagogical material is published by the more education-focused American Journal of Physics.
Upvotes: 1
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2023/08/16
| 1,713
| 7,328
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<issue_start>username_0: I am close to finishing my PhD and most likely will have 1 or 2 papers published. For personal reasons I have to take around 2 year break from academia, but I would like to come back for a postdoc. People around me keep telling me that if I get out, I can't come back in, especially because the groups I want to apply to are really good (I chose them for the subject, not prestige, but the point still stands).
Is that true? I will still try, but in case that is accurate, does anybody have advice in how to make the transition or any strategies that worked for other people? I am afraid of wasting my hard work and sacrifices.<issue_comment>username_1: More clarification is needed here since this very much depends on the field you are in and what type of break you intend. In machine learning, it is not uncommon for people to go take on an industry position for a couple of years before returning to an academic position. The idea is that the industry position equips them better to tackle translation tasks or acquire skills in large-scale software engineering.
Other fields might be more or less malleable. A general recommendation from my side would be to not worry unduly. If your reasons are personal and important to you, would the knowledge that you may not get another position afterwards change the decision? If not, I'd just go ahead with it and see where it leads you.
Best of luck!
Upvotes: 2 <issue_comment>username_2: One problem with a break is that you might lose contact with those people who can best support your return. Coming back to academia might require good and honest letters of recommendation confirming your likelihood of success.
I recommend two things, though related.
Keep in contact with people, especially your advisor, but also other faculty members.
But, just as important, keep up with ideas in your field and spend some effort discussing them with others, such as those mentioned above. You don't want to be two years behind the curve when you reenter. I suggest keeping a notebook of ideas, especially those that might lead to future research. Read a few papers. Ask people to keep you informed of progress in the field.
Upvotes: 4 <issue_comment>username_3: The answer ranges from "mildly difficult" to "very difficult", but does not reach the extremes of "no consequences" or "impossible."
First what is your reason? If you are a cancer patient undergoing chemotherapy, have to take care of elderly parents, etc., then do what you have to do and then come back to academia. It's not a fair system and things will be harder for you than for people who were working those two years, but far from impossible. This, of course, depends on the field. In some fields, you should be able to at least keep up with things by reading the journals, attending conferences virtually, and keeping up with colleagues. In other fields, e.g. in advanced laboratories, things change so quickly that by the time you read it in the journals, it's obsolete. Regardless, when you return, you can write on applications the reason for the hiatus (e.g. family medical situation), and explain that it's *solved*. Everyone wants to be understanding of past crises, but nobody wants to hire someone who is in the middle of one.
A lot of people take breaks from academia for reasons which are arguably optional: a "mental health break", a long-planned hiking or cycling trip across the continent, marriage, having kids, etc. And before everyone jumps in about how unfair this is and how it affects some groups more than others, etc., please take a second to notice that I am not advocating or justifying the system, but explaining to the OP how these reasons are in fact, usually seen as optional. You can make your own decision as to your life priorities. If taking a mental health break will save your live, by all means do it. If having children is more important than whatever consequences you reap from the break, by all means do it (on the latter, I'd agree with you.) And so on. If your reason for the break falls into what could be considered optional life choices, then make your decision based on that. Just don't expect it to be without consequences.
Upvotes: 3 <issue_comment>username_4: My situation is perhaps anecdotal and likely different, but shows that it is not impossible, though, as others have mentioned, this may depend on many factors such as field etc.
To make my contribution less anecdotal:
* Try to show you are still enthusiastic about research. At least: read. Better yet: try to publish; even if not very impactful or outside of the field you want to get back in. It shows general skills: you still have fresh ideas and can communicate them. A preprint or some blog posts can also suffice to showcase this. Get it out there.
* Retain your academic connections, establish new, or reestablish old ones.
* You may have to start a bit *low* on the ladder: less reputable lab, short-term position, etc. It will be easier to get in, and may require hard work, but try to work your way up from there if you cannot get into your preferred lab. I would not recommend it, but know of people who did a second PhD in a related field because they really wanted back in.
Personal experience:
I obtained my PhD, then worked a *research position* for about 3 1/2 years at a government agency. The position turned out to be not very research-heavy: I learned a lot but did not do research and did not publish in the first 2 1/2 years. Then decided the research part really was an itch, and started looking for a post-doc. How did I manage to get back in?
First, it took me about a year to find a relevant position, though I did not want to move cities which was a very big limiting factor.
Second, the position is just for a year and in a lab headed by someone I knew from my PhD (not an advisor). As argued by others, connections matter. It is a rather young lab without a big reputation (yet), which means it might be easier to get in. Most importantly, the work is interesting and relevant. A recommendation letter from my former advisor (note, I did not hear anything from him for three years, but he was still happy to write a letter) was likely important.
Third, wanting to get back in, I published two manuscripts related to work I did in my government agency position, showing that I can still do the trick. This took some of my personal time though. They were not directly relevant for the position I hold now, but they were more or less in the same general field, and in *good* specialized journals.
Upvotes: 2 <issue_comment>username_5: It is possible to maintain an unpaid affiliation with a university. The length of time that the status can be maintained is dependent on the university and other circumstances. You can ask your advisor or the head of your department for an affiliation status. I would recommend to try to stay mildly involved in research projects during that time to maintain an authorship record.
Another suggestion is to ask to stay in the department as an adjunct instructor if possible. Doing one course a semester can be a light workload and a small amount of income and this will maintain an affiliation with the university. This is, again, something to discuss with your advisor or the head of your department.
Upvotes: 2
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2023/08/16
| 1,169
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<issue_start>username_0: I emailed an famous professor a paper (say paper B) that corrects a critical mistake in their old, well-received paper (say paper A). I invite them to coauthor. They neither agree nor disagree. They told me that they were not entirely convinced and had me wait. After waiting for more than two months, they come back to me with a new plan written:
1. They want to completely rewrite paper A, adding many more new materials
2. They ask me to coauthor with them
3. They want to add another coauthor, Jason, because Jason **independently** discovered similar results as mine.
Note that my discovery is partly published on preprint and Jason's claimed contribution is very similar to my published ones. Jason claims to "never seen my preprint".
In my field every coauthor is equal; there is no first author. Their request is different from what I propose. Their email is written in an affirmative tone rather than an “advising/inquiring” tone.
I worked on this problem for 19 months and shared with many researchers. There is a preprint I posted online dated 2021. So I don't believe Jason independently come to the same result.
I don't know if this is normal for academia. I don't know what to do. I haven't agree or disagree with their proposal yet. What's my best actions here?
Clarification: I don't think the famous Professor is lying. I think he is honest in transmitting information. It is possible to me that Jason is not 100% honest here.<issue_comment>username_1: What you are being offered is very reasonable, if you feel like you should publish independently you can go ahead.
But keep in mind that in doing so you will start a race where you can only lose [1] between you and the team "famous professor + Jason". It is quite likely that no one will care about your correction of famous professor work, because they already have a correction for their own work.
[1] if you publish in the same year as them, in the future it will not be clear who published it first, so most likely the professor publication will be judged as "heavier", if you publish the correction before them ... apart from a small burst in interest, then your publication will be superseeded by their own. If you publish after them ... well, good luck in finding someone interested in your work apart from some Master thesis doing literature study.
Upvotes: 2 <issue_comment>username_2: If your preprint already contains parts that are relevant to the new paper you're working on, **you can cite it in a new paper**. No credit is lost for the work that you've already posted. It's okay if that preprint never becomes its own separate published paper besides the one you coauthor with the professor and Jason, it's still something that can be cited.
I think it's far more likely that you benefit from coauthoring this additional paper versus turning it into a race and contest, not only in terms of the "credit" for the work but also for your reputation in the field for working well with others. It's very reasonable and understandable to anyone that Jason would have come up with what he did on his own, without your preprint.
The professor is doing a good diplomatic job of making the best of the situation for all three of you by suggesting a collective collaboration; imagine if Jason were the one writing this post and said, "I discovered something new and tried to collaborate on it with a professor that the work was building on, but now they're taking my idea and publishing it with some other person they said emailed them before me!"
If the work you had already done on this problem was complete, you could have just published it already. Instead, it will most likely benefit from the extra polish that comes with collaboration. I would recommend setting clear expectations with your collaborators regarding who is responsible for which part of the new manuscript to make sure the remaining work is distributed equitably.
Upvotes: 1 <issue_comment>username_3: A few years ago I found a group working on the same problem I worked on. My code had been online for years, and so was theirs. I looked through and was shocked by how similar their code was to mine -- parts were even line-for-line identical!
I *didn't* think "they stole my code!"
I thought instead "well great minds think alike! Turns out my way of solving those problems was so obvious and right that someone else thought of it too."
I was still very nervous about approaching them and pointing out that we were working on very similar things. Thankfully, they reached out to me and asked if we wanted to work together. I jumped at the opportunity and today continue to collaborate with them on maintaining and upgrading what is now a joint code. Twice as many coders means half the work for each of us!
The benefit of a good collaboration far outweighs any benefits of being a sole author. You should focus on how to keep this collaboration being open, productive and pleasant, and not on some idea of "sole glory".
Upvotes: 3
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2023/08/16
| 1,454
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<issue_start>username_0: My idea would be to build a theoretical classification similar to Kardashev's ladder to consider what is scientific, what is not scientific or what is pseudoscientific.
***The Kardashev scale definition would look something like this:***
>
> "The Kardashev scale is a theoretical classification proposed by Russian astrophysicist <NAME> in 1964 to measure the level of technological development of an alien civilization. The scale is based on the amount of energy a civilization is able to collect and use, and is divided into different levels."
>
>
>
Whereas today there are many different research methods, argumentative methods, academic validation methods and tests with a certain percurlarity, difference. Would it be possible to create a theoretical model to classify scientific articles?
**Initial considerations**
**1.** Some scientists, academics, philosophers, intellectuals, thinkers may think that the production of a theoretical classification of scientific articles can produce, instead of greater scientific and academic rigor, a tool for manipulating data, statistics and studies.
**2.** Some people might be skeptical that such a tool would be possible to make, as knowledge and methods can change over time.
**3.** This initial question is who is writing the first scientific article and would like some help about different authors and proposals or scientific methods. For example, initially I'm thinking of doing a literature review research on different types of scientific, academic and philosophical methods in scientific production. In this sense, I think of starting with <NAME>, since he is well known and his falsifiability method, as far as I know it today, is still used to some extent. One of my current problems is what alternatives do we have to validate, to make a certain scientific article reliable?
**4.** I hope initially or previously to use the "Kardashev scale" as a starting point to define the problem of demarcation: "what is science, what is not science, what is pseudoscience". This would be interesting to analyze the degree of accuracy with which a certain level of knowledge is made, produced or used in society. On this data, "we can validate or accept certain knowledge along with a certain ethics, public morals. In the sense of a common, collective, greater good or according to the laws and the constitution that we honor in the sense of consensus, argumentation, discussion, problematization of ideas".
**5.** Is there any area of study that analyzes, measures, produces curation or review scientific production? If yes, what is the name of this field of study? If this field of study does not exist, how to produce a scientific article in the best way? without a cognitive bias? How many or what criteria could I use when producing or analyzing a scientific article?<issue_comment>username_1: What you are being offered is very reasonable, if you feel like you should publish independently you can go ahead.
But keep in mind that in doing so you will start a race where you can only lose [1] between you and the team "famous professor + Jason". It is quite likely that no one will care about your correction of famous professor work, because they already have a correction for their own work.
[1] if you publish in the same year as them, in the future it will not be clear who published it first, so most likely the professor publication will be judged as "heavier", if you publish the correction before them ... apart from a small burst in interest, then your publication will be superseeded by their own. If you publish after them ... well, good luck in finding someone interested in your work apart from some Master thesis doing literature study.
Upvotes: 2 <issue_comment>username_2: If your preprint already contains parts that are relevant to the new paper you're working on, **you can cite it in a new paper**. No credit is lost for the work that you've already posted. It's okay if that preprint never becomes its own separate published paper besides the one you coauthor with the professor and Jason, it's still something that can be cited.
I think it's far more likely that you benefit from coauthoring this additional paper versus turning it into a race and contest, not only in terms of the "credit" for the work but also for your reputation in the field for working well with others. It's very reasonable and understandable to anyone that Jason would have come up with what he did on his own, without your preprint.
The professor is doing a good diplomatic job of making the best of the situation for all three of you by suggesting a collective collaboration; imagine if Jason were the one writing this post and said, "I discovered something new and tried to collaborate on it with a professor that the work was building on, but now they're taking my idea and publishing it with some other person they said emailed them before me!"
If the work you had already done on this problem was complete, you could have just published it already. Instead, it will most likely benefit from the extra polish that comes with collaboration. I would recommend setting clear expectations with your collaborators regarding who is responsible for which part of the new manuscript to make sure the remaining work is distributed equitably.
Upvotes: 1 <issue_comment>username_3: A few years ago I found a group working on the same problem I worked on. My code had been online for years, and so was theirs. I looked through and was shocked by how similar their code was to mine -- parts were even line-for-line identical!
I *didn't* think "they stole my code!"
I thought instead "well great minds think alike! Turns out my way of solving those problems was so obvious and right that someone else thought of it too."
I was still very nervous about approaching them and pointing out that we were working on very similar things. Thankfully, they reached out to me and asked if we wanted to work together. I jumped at the opportunity and today continue to collaborate with them on maintaining and upgrading what is now a joint code. Twice as many coders means half the work for each of us!
The benefit of a good collaboration far outweighs any benefits of being a sole author. You should focus on how to keep this collaboration being open, productive and pleasant, and not on some idea of "sole glory".
Upvotes: 3
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2023/08/17
| 825
| 3,523
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<issue_start>username_0: I'm trying to figure out the path I take when I return to my PhD (UK). I want to develop research skills and 'capability' in an area of physics that is not my thesis title. I've asked multiple times to change focus but the answer is always no.
I've already published a single author paper at an international conference on something that wasn't related to my thesis title, and I would like to take it further.
What are the consequences of not following instructions from supervisors?
(As far as I can tell, the only way they can fire me is if I fail the internal check points for thesis progress, but with my topic you'd really have to do *no* work at all; I'm more advocating like going 50/50 or maybe a bit more)<issue_comment>username_1: I suggest that you prioritize your degree completion and keep your advisor(s) happy about that.
But there is nothing in academia that says you should turn your brain off to other thoughts.
In fact it is useful to keep a notebook of thoughts for future study/research, with a separate "page" per topic and that you revisit it periodically or whenever some new thought occurs to you.
And, the sooner you finish, the sooner you can set your own path.
But if you have a setback in completion of your thesis you will be in a very bad spot. First things first. Let the rest happen as it must.
Upvotes: 3 <issue_comment>username_2: First, make sure that you are not in the crank zone. The fact that you already published at a conference makes one think you are not just a crank thinking they know better than their advisor "just because." So assuming that you are on solid ground:
It takes a very confident, generous, and wise advisor to accept the deal you are offering. You are suggesting to continue getting whatever benefits you are getting while minimizing what your advisor is getting back. So your advisor's response is not unreasonable.
Having said that, you do what you have to do. The consequences you will face will depend on your publication output. If you end up just doing the minimum for your advisor while publishing a dozen papers in the other field, your advisor will be pissed, but you win. If you end up doing the minimum for your advisor and only getting mediocre work published in the other field, it's a lose-lose. Ideally, you'll publish good stuff with your advisor while keeping a foot on the other field, and that's a win-win.
Upvotes: 1 <issue_comment>username_3: You have not mention what what the reason of your changing interests. Why you have entered a PhD program if you do not like the topic?
Anyway, even though you have different research interests, you cannot change the topic of your thesis at will. There are constraints. The major one is the funding. This you have already mentioned that in your comments.
The second one, you need some supervision in any case. It is not possible to do science solo. You might get some impression of the progress because the progress is faster at the beginning. But sooner or later you will face difficulties and will have no one to discuss. But even the selection of topic for your solo research is not that unambiguous. You need to communicate with people with a broader vision.
I strongly discourage you of going this way. Please, focus on producing excellent thesis in the planned topic. If this does not appeal to you, there is only one solution, change the PhD program and supervisor. To stay in the program and doing something different is even morally wrong.
Upvotes: -1
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<issue_start>username_0: I sent an email with my qualifications to a prospective PhD supervisor and he responded by asking for my availability for interview and the likely days of the week, this could hold. I responded that I am available for interview and also chose a day from the available days he gave.
He didn't reply to my email. I sent a reminder a day before the interview day asking for the link for the interview session and the time of the day when the interview will hold but there was also no response. Please, what could have happened?<issue_comment>username_1: I suggest that you prioritize your degree completion and keep your advisor(s) happy about that.
But there is nothing in academia that says you should turn your brain off to other thoughts.
In fact it is useful to keep a notebook of thoughts for future study/research, with a separate "page" per topic and that you revisit it periodically or whenever some new thought occurs to you.
And, the sooner you finish, the sooner you can set your own path.
But if you have a setback in completion of your thesis you will be in a very bad spot. First things first. Let the rest happen as it must.
Upvotes: 3 <issue_comment>username_2: First, make sure that you are not in the crank zone. The fact that you already published at a conference makes one think you are not just a crank thinking they know better than their advisor "just because." So assuming that you are on solid ground:
It takes a very confident, generous, and wise advisor to accept the deal you are offering. You are suggesting to continue getting whatever benefits you are getting while minimizing what your advisor is getting back. So your advisor's response is not unreasonable.
Having said that, you do what you have to do. The consequences you will face will depend on your publication output. If you end up just doing the minimum for your advisor while publishing a dozen papers in the other field, your advisor will be pissed, but you win. If you end up doing the minimum for your advisor and only getting mediocre work published in the other field, it's a lose-lose. Ideally, you'll publish good stuff with your advisor while keeping a foot on the other field, and that's a win-win.
Upvotes: 1 <issue_comment>username_3: You have not mention what what the reason of your changing interests. Why you have entered a PhD program if you do not like the topic?
Anyway, even though you have different research interests, you cannot change the topic of your thesis at will. There are constraints. The major one is the funding. This you have already mentioned that in your comments.
The second one, you need some supervision in any case. It is not possible to do science solo. You might get some impression of the progress because the progress is faster at the beginning. But sooner or later you will face difficulties and will have no one to discuss. But even the selection of topic for your solo research is not that unambiguous. You need to communicate with people with a broader vision.
I strongly discourage you of going this way. Please, focus on producing excellent thesis in the planned topic. If this does not appeal to you, there is only one solution, change the PhD program and supervisor. To stay in the program and doing something different is even morally wrong.
Upvotes: -1
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2023/08/17
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<issue_start>username_0: My uni advisor offered me, some months after my graduation, a PhD position in his group. I do not know any detail about such position.
Right now I am more inclined going in different topics, and I am actually evaluating other proposals, academic and not. Still, since an intersection with my current interests is somewhat possible, I would like to know what their project might involve, but with the serious possibility that I will reject the proposal.
I was thinking of writing something along the lines of "thanks for the message, I am thinking about other proposals in a different direction. Could you please give more details".
Do you think this is appropriate? Would you set up the reply in a different way? Thanks!<issue_comment>username_1: I suggest, pretty strongly, that you request a face-to-face meeting to "discuss your future".
Assuming that you have established trust with the person, as seems to be the case, ask them for the details you seek, but also bring up other possibilities and ask for their advice.
An ethical advisor would give advice to your benefit, not their own.
And even if you take another offer, such meetings are useful in maintaining long term contact that can benefit you in the future. But such things are much harder by email where a misplaced word can cause misunderstandings. Make it personal, not impersonal.
Upvotes: 2 <issue_comment>username_2: You go ahead and ask for more details from your advisor. It's a reasonable request. What you seem to want is to explore other options while leaving this door open. You don't know the details of your advisor's offer, and presumably, you don't know the details of the other options either. So right now you don't even know your options, as you are in the information-gathering stage.
Some people have the mistaken perception that in negotiations, all parties give their "best and last offer" (in real estate jargon) up front, so that you can just enter all the options on a spreadsheet and make a decision. But that's not how anything goes. Most negotiations, like the one you are about to undergo, develop in stages: people send 'feelers' around to see what's available and who's interested (this seems to be your stage now), then if things sound good, all parties ask for more information. You then ask your advisor about the stipend, how much TAing is involved, which project you'll work on and who will have ownership (e.g. will it be your own project or will you be a postoc's helper?), etc. Your prospective advisor will ask about your interests, your time commitment, your requirements for pay and TAing, etc. Presumably you both have other options, that is, you have other positions to consider, and your prospective advisor has other candidates. You keep dancing until an agreement is made.
Upvotes: 2 [selected_answer]
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2023/08/17
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<issue_start>username_0: **Synopsis**: Can a fake journal keep the copyright of a submitted (**not** published) paper, despite the authors' request to withdraw it (because of the journal not keeping its full-waiver promise and also not following a correct article processing routine)?
Is this legally possible for the **thief** to legally keep the **theft** (and **un**published) article? Or can the authors ignore the previous journal's threats, and submit the paper to another journal?
The authors have paid no fee and will not pay any. But they want their paper back, so that they can submit it to another journal.
---
**Details**:
1. My friends submitted their paper to a legit-looking journal, on the condition that it has no article processing charges (APC) and fees, if accepted.
2. The journal agreed with no-fee request; they received the manuscript, and despite its promise of speed, it did nothing for 7 months. After 7 months, the authors asked about their paper, and due to the journal's lack of response, the authors withdrew the paper.
3. The journal replied after the withdrawal request that: it is accepted and in proofing stage (without any peer-review or revisions or even without any acceptance letter!). The journal asked for 1200 Euros to publish the paper.
4. The authors reminded the journal of their condition of No-APC.
5. The journal gave some untrue (completely provable), again asking for APC.
6. The authors asked for withdrawal again.
7. The journal refused, unless the authors pay about 700 Euros. The journal told the authors they are not allowed to submit their paper to any other journal because it is with the (predatory) journal and the **journal has the copyright now**. **Is this possible?**
* **NOTE**: Upon the submission, the authors have told the journal that the paper is not submitted to any other journal and under consideration anywhere. Can the journal abuse this statement to keep the theft material?
* **NOTE**: **No copyright** transfer was signed or sent to the journal upon submission.
* **NOTE** that the journal as well is bound to publishing the paper (if peer-reviewed and accepted) without any APC, as per their agreement with the authors.
* **NOTE** that the journal has not even peer-reviewed the paper!
* **NOTE**: The journal had not even accepted the paper (there is no acceptance email)!
* **NOTE**: The journal is open access and its website states that the authors retain the copyright (not that their website is authentic or that they follow their own guidelines, but even their website does not say anything about automatically transferring any copyrights to the journal upon the submission).
* **NOTE**: The journal rushed to hastily accept the paper (without any peer review or revision) **AFTER** the authors' withdrawal. First, the authors sent 2 emails to the journal, requesting to withdraw the paper. Then, the journal said "the paper is in proofing stage and pending payment" (despite the no-payment agreement). **So one may say that the paper was withdrawn BEFORE the (so-called) acceptance, right?**
**Questions**:
1. Can the authors ignore the journal and submit the paper to another journal?
2. If so, how?
3. If not, what should be done?
4. What else should the authors do? For example, if they want to sue the journal, how should they do so?
ps. I see David's answer in this thread may be relevant to my question. The difference is that my friends' paper is not published (nor peer reviewed): [How can I withdraw a publication from a predatory (fake) journal and resubmit to a legitimate journal?](https://academia.stackexchange.com/questions/17374/how-can-i-withdraw-a-publication-from-a-predatory-fake-journal-and-resubmit-to)<issue_comment>username_1: The journal has nothing to "give back" and no basis for demanding payment. As long as the authors still hold copyright the work is theirs and theirs alone.
All that is required is a communication that you are withdrawing the paper from further consideration. While it is good to wait for confirmation that they have received your withdrawal, you don't need their agreement.
A submission is an "offer" not a gift. You offered them something of value but they put conditions on acceptance that you don't like. That is on them.
Also, the journal doesn't need to be predatory for the above to be valid.
Upvotes: 6 <issue_comment>username_2: >
> Is this legally possible for the thief to legally keep the theft (and unpublished) article?
>
>
>
A more relevant question would be: Can someone libel me and legally get away with it? The answer is yes, they can, if you cannot find them. In most cases it is not practical to enforce laws or contracts broken by a predatory journal. You probably cannot even find out what country they are in.
If their web host happens to be in the US, if they chose to publish the paper without your consent you could send the host a DMCA notice to remove a published article. All this does is prompt a malicious publisher to change hosts.
* Can the authors ignore the journal and submit the paper to another journal?
Yes.
* If so, how?
You already withdrew the manuscript. Just submit it to another journal saying "this manuscript was withdrawn by the authors from consideration at another journal." No details are needed.
* What else should the authors do?
Check the reputation of journals more carefully before you submit.
* For example, if they want to sue the journal, how should they do so?
That would be a waste of money, even if you can locate them.
Upvotes: 4 <issue_comment>username_3: In addition to the excellent answers by username_1 and username_2, I will add a few points. For the sake of completeness, let me summarize the key issues I see here. I am not a lawyer, but I do have a decent understanding of copyright law:
* As long as you did not formally transfer the copyright or grant a formal licence (e.g., signing a document that explicitly says that you transferred the copyright or that you explicitly authorize publication), you retain full copyright. No matter how much work the journal does or does not do on your manuscript (e.g., legitimate peer review and full copy editing), as long as you have not transferred copyright, you retain full ownership of your manuscript and you can do whatever you want with it, including withdraw it.
* Your formal notice of withdrawal is all that you need to do to fulfill your ethical obligation of not submitting to two journals at the same time. It does not matter if the first journal refuses to withdraw the article from consideration. They have no right to do anything with your article (since you did not give them any legal right beyond merely reviewing the manuscript).
* As long as they do not publish the manuscript, their threats mean nothing. However, they are not allowed to publish your manuscript without your permission. That would be a copyright violation and you could sue them for that. They know this, so they will probably not do anything beyond empty threats. It is annoying, but you can safely ignore them.
* Considering submitting to other journals, you can safely say that your manuscript is not under consideration in any other outlet. As far as you are concerned, that is true. (And considering that they probably did not even peer-review your manuscript, that is even doubly true.) You should probably NOT mention anything about the predatory journal--just say that your manuscript is not under review elsewhere.
* In the worst-case but highly unlikely scenario, the predatory journal might contact the journal in which you eventually publish to say something. If they do that, simply send the new editor your history of communications. That should be sufficient for any reasonable editor. Their main concern would be that you did not sign any copyright statements with the predatory journal. As long as you did not do that, there should be no problem.
Upvotes: 5 <issue_comment>username_4: I disagree with other answers with regard to whether you can resubmit elsewhere. My personal opinion is that if you know the paper is being published elsewhere, legally or not, you have the responsibility to at least tell your target journal about the situation when you resubmit.
Upvotes: -1 <issue_comment>username_5: I'll offer a different perspective as to what usually happens when the new journal receives your "duplicate submission". The [standard COPE guidelines look like so](https://resource-cms.springernature.com/springer-cms/rest/v1/content/4246/data/v2):
[](https://i.stack.imgur.com/IGZiO.png)
I highlight the key step. *Even if the new journal suspects duplicate publication, you are given a chance to defend yourself*. That's when you show the new journal all the correspondence you had with the original journal, which will quickly land you in the "satisfactory explanation" box, and the review process will proceed as normal. The old journal cannot stop publication; they can only trigger an investigation.
Be sure to keep the correspondence, in case it really comes down to an investigation. You could also include the correspondence in the cover letter when you submit, which might pre-empt any suspicion.
Upvotes: 4
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2023/08/17
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<issue_start>username_0: I'm applying for a job at an elite women's liberal arts college, which is part of a co-ed group of liberal arts colleges where students can easily take classes at any of these colleges (in the humanities, if that's helpful).
I assume it'd be pretty essential to address the fact that the job is at a women's college - but what can I possibly say that isn't trite (despite being true)? Of course, it'd be a joy to teach intelligent women and help them develop their academic interests in this unique setting - who wouldn't think so? What can I say?
If anyone has any experience of teaching at a women's liberal arts college: what made it special for you? (regardless of whether it would be useful for the job application)<issue_comment>username_1: While I haven't taught at such a college, my daughter attended one. I don't think you need to specifically address that it is a women's college, but rather that you are qualified to teach great, hard working, demanding students.
Such colleges, like other elite colleges, are small enough that they can demand excellence from their faculty. The focus is on teaching, but research, especially that open to undergraduates is also highly valued.
What makes elite women's colleges "special" is that there isn't a lot of sexist BS that occurs in the greater world and tries to "put women in their place". These students know their "place" and it isn't at the bottom (or the kitchen, unless they really choose that). The college will likely be a highly supportive environment in which the students (some of which are trans women these days) can find their own path to excellence.
---
I have some experience as a visitor at an elite college, though it was co-ed. The students are very demanding of high quality instruction and accepting of hard work. They come in smart and eager. You need to support that. I'd suggest that is where you put your focus in an application. They will be more interested in beginning research opportunities than the typical college student. Many of their parents will be academics. Very high standards.
Upvotes: 2 <issue_comment>username_2: You have two questions, so I'll answer separately:
1. **What can I possibly say that isn't trite (despite being true)?** There are as many criteria for evaluating application essays are there are faculty sitting in those committees. I've sat in many faculty search committees, and chaired a good portion of them, and my general feel is that these questions on the application materials are there to answer two issues: (1) Are you not crazy?, and (2) Did you do your homework? In other words, the essays are there to screen bad candidates, not to select the good ones. I've never seen a committee make an offer to a candidate based on the essay. Any well written answer, with no grammatical errors, that addresses the type of university we are (e.g. research vs. teaching; small vs. large; residential vs. commuter; elite vs. open admissions, etc.) gets the pass.
2. **What made it special for you? (regardless of whether it would be useful for the job application)**. I have not taught at an elite women's college, but I have several colleagues who have, and some who still are teaching there as full tenured professors. I do have experience teaching at small and large elite universities. If you get the job, what you might find is that these colleges are in many ways, just like everywhere else in academia. Just because the faculty are proportionally more women than men, does not diminish the petty fights, the political positioning, the social climbing, the backstabbing, etc. normal in similar co-ed institutions. Based on the stories from the friends who taught and still teach there, it seems that the level of student entitlement is above average (read: immense pressure on professors to just give As to everybody resulting in ridiculous levels of grade inflation, impossible to bring a disciplinary case against a student, US culture wars stuff, etc.) On the bright side, they also have all the benefits of elite institutions, like good funding, job security, respect for the liberal arts, etc.
Upvotes: 3 <issue_comment>username_3: Your job application is about why they should hire you. It is not about what you enjoy.
My field has poorly served female students. There are evidence-based methods of helping female students learn (they also work for other students). If you are working in my field, you might describe how you use those methods. This would apply to any faculty job application at a coed college too.
A faculty member who taught physics at a women's college said teaching there is the same - that seems very logical.
Do mention the other aspects of the college that are unique and why your skills contribute to them.
Upvotes: 2
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2023/08/17
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<issue_start>username_0: I am planning on applying for PHD's in the UK over the next 12 months - Criminology PHD's specifically.
What is dissuading me is the funding situation. International Students do not have their tuition fees fully covered by their funding stipend and therefore will incur hefty fees.
I am a Republic of Ireland national, which actually falls under domestic fees in the UK - **however, I have not been resident in Ireland or the UK for the past 3 years, which is one of the stipulations to benefit from domestic fees. I have been resident in Germany since 2018 and currently live there.**
Before I potentially waste hours upon hours in the application (s) process, I want to get feedback as to what my realistic options are. I have no desire to go down the self funded route at this point.
1. What exact funding options for International Students and how common are they? Keep in mind I have been out of academia for many years, completed my M.A. in 2015, and therefore not the ideal candidate regardless of how interesting or good my research proposal is.
2. What if I moved to Ireland or the UK in the next 6 months, would this help with my residency status? This is a move I am considering any ways as I wish to be closer to home after quite a while abroad. **However, my understanding is that the requirement is to have been based in the UK or Republic of Ireland for the past 3 years.**
I want to do a PHD because I have a genuine love for research and writing, it feels truly me, and therefore would love to make this work. Unfortunately it seems nearly all Criminology PHD's in Europe are based in the UK, so I am not sure what other options exist.<issue_comment>username_1: While I haven't taught at such a college, my daughter attended one. I don't think you need to specifically address that it is a women's college, but rather that you are qualified to teach great, hard working, demanding students.
Such colleges, like other elite colleges, are small enough that they can demand excellence from their faculty. The focus is on teaching, but research, especially that open to undergraduates is also highly valued.
What makes elite women's colleges "special" is that there isn't a lot of sexist BS that occurs in the greater world and tries to "put women in their place". These students know their "place" and it isn't at the bottom (or the kitchen, unless they really choose that). The college will likely be a highly supportive environment in which the students (some of which are trans women these days) can find their own path to excellence.
---
I have some experience as a visitor at an elite college, though it was co-ed. The students are very demanding of high quality instruction and accepting of hard work. They come in smart and eager. You need to support that. I'd suggest that is where you put your focus in an application. They will be more interested in beginning research opportunities than the typical college student. Many of their parents will be academics. Very high standards.
Upvotes: 2 <issue_comment>username_2: You have two questions, so I'll answer separately:
1. **What can I possibly say that isn't trite (despite being true)?** There are as many criteria for evaluating application essays are there are faculty sitting in those committees. I've sat in many faculty search committees, and chaired a good portion of them, and my general feel is that these questions on the application materials are there to answer two issues: (1) Are you not crazy?, and (2) Did you do your homework? In other words, the essays are there to screen bad candidates, not to select the good ones. I've never seen a committee make an offer to a candidate based on the essay. Any well written answer, with no grammatical errors, that addresses the type of university we are (e.g. research vs. teaching; small vs. large; residential vs. commuter; elite vs. open admissions, etc.) gets the pass.
2. **What made it special for you? (regardless of whether it would be useful for the job application)**. I have not taught at an elite women's college, but I have several colleagues who have, and some who still are teaching there as full tenured professors. I do have experience teaching at small and large elite universities. If you get the job, what you might find is that these colleges are in many ways, just like everywhere else in academia. Just because the faculty are proportionally more women than men, does not diminish the petty fights, the political positioning, the social climbing, the backstabbing, etc. normal in similar co-ed institutions. Based on the stories from the friends who taught and still teach there, it seems that the level of student entitlement is above average (read: immense pressure on professors to just give As to everybody resulting in ridiculous levels of grade inflation, impossible to bring a disciplinary case against a student, US culture wars stuff, etc.) On the bright side, they also have all the benefits of elite institutions, like good funding, job security, respect for the liberal arts, etc.
Upvotes: 3 <issue_comment>username_3: Your job application is about why they should hire you. It is not about what you enjoy.
My field has poorly served female students. There are evidence-based methods of helping female students learn (they also work for other students). If you are working in my field, you might describe how you use those methods. This would apply to any faculty job application at a coed college too.
A faculty member who taught physics at a women's college said teaching there is the same - that seems very logical.
Do mention the other aspects of the college that are unique and why your skills contribute to them.
Upvotes: 2
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2023/08/18
| 537
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<issue_start>username_0: Many journals choose single anonymized review processing instead of double anonymized. I wonder what are the considerations behind these decisions to choose the single anonymized review?<issue_comment>username_1: The big advantage of single-blind review is ease. You do not have to anonymize the text before sending it for review (even anonymized, [it's reasonably easy to identify the authors, especially with Google](https://academia.stackexchange.com/questions/156016/double-blind-peer-review-authorship-can-be-inferred-from-the-manuscript) It's even trivially easy if the authors upload a preprint.).
The other main reason, I think, is less noble. At some level people *want* to base their decisions on secondary factors like the identity of the author/reviewer. Examples are:
* If the author is a well-known crank, then one might want to desk reject even if the paper at surface level looks like a serious piece of work.
* If the author is a Big Name, one might be more inclined to agree to review the paper.
* If the authors are undergraduates, one might be more lenient.
* If the author is an expert on the general topic, then even if the paper is radical, one might be more inclined to accept it.
Which is of course how bias manifests itself. But when things really boil down to a judgment call, it's extremely tempting to seek this information.
Upvotes: 6 [selected_answer]<issue_comment>username_2: Your question is based on the wrong premise: That journals make an explicit decision to go with single-blind protocols. In reality, however, they use this approach because that's how it has always been done -- one would need to make an explicit decision to *move away* from this approach.
So the question then is: Do journals see sufficient benefit to switching to double-blind reviews to justify the added complexity in workflows for authors, editors, and support staff. Apparently, a substantial number of journal editors do not see sufficient value in this. (Whether that is an *objective* assessment of the situation may be debatable. But the decision is made by people, and so at the end of the day, the decision is made based on the *subjective* assessment of an editor or publisher.)
Upvotes: 4
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2023/08/18
| 783
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<issue_start>username_0: I have a not enough checked for errors proof of an important math conjecture, P=NP (for your calmness: the proof is not very constructive). 8 pages.
Where can I post it for scrutinized checking?
I posted it and the question to check the proof in ResearchGate.net. I tried to post it at PhysicsForums.com but my question was deleted. I posted it on Reddit, with no useful responses. Where else?
I also negotiated to check it for $100 at Fiverr. It's not very small sum and I doubt whether to spend it.
I can't post on arXiv, because I am not affiliated with an institute.
I do realize that the final destination is a peer-reviewed journal. But I want feedback *before* I submit it to a journal.<issue_comment>username_1: The reason you are not getting any answers is that P=NP is right there in crank-land along with proofs against evolution, the 2nd law of thermodynamics, general relativity, etc. Nobody wants to even look at your proof because what you are asking is to be educated in some very basic concepts in computer science (or biology, or physics, etc.)
This is not to discourage you, or to say that outsiders cannot make important contributions. It's that you need to do some homework before expecting others to take you seriously.
[Is there a single example of an outsider considered a "crank" publishing a ground-breaking result that was found to be correct (in the last 30 years)?](https://academia.stackexchange.com/questions/181336/is-there-a-single-example-of-an-outsider-considered-a-crank-publishing-a-groun)
[I believe I have solved a famous open problem. How do I convince people in the field that I am not a crank?](https://academia.stackexchange.com/questions/18491/i-believe-i-have-solved-a-famous-open-problem-how-do-i-convince-people-in-the-f)
Upvotes: 4 <issue_comment>username_2: In theory, there is a way to get your proof fully verified without the cooperation of other people, namely formal verification. That would involve first formalizing the statement that P=NP, and then proving that statement to the satisfaction of a proof verifier (Lean, maybe?).
Formalizing the statement is in itself not going to be easy but I would expect someone willing to learn a suitable formal system who is very persistent about it to eventually succeed; the project could be made fairly concrete by saying e.g. that Levin's universal algorithm halts in polynomial time on SAT. I think once that is done, someone who has a short correct proof would also eventually succeed in formalizing *that*, albeit not without significant additional work.
It is however probable that *finding a flaw* in your proof is far easier. One approach for doing so automatically could be to show your proof to a system like GPT-4 and asking it to highlight the least plausible bit of the argument. While it would certainly not be able to verify the proof, it might just succeed in spotting a part of the argument that is in contradiction to established knowledge or intuitions, and if so, such feedback might be easy for you to verify.
Upvotes: 2
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2023/08/18
| 574
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<issue_start>username_0: I recently submitted my first paper to a well-known journal in the field. After about 1.5 months, the first decision was a major revision which I completed promptly and re-submitted (the decision was by a single reviewer, and of course, the editor).
After about another month the same reviewer asked for a moderate revision (also commenting that the main issue of the major revision had been satisfactorily cleared). I again acted on it quickly and re-submitted.
This new version was sent back to the same reviewer again, who, after two days, remarked to the assistant editor that they might want to get a second opinion and so the AE is looking for another reviewer.
Since it is my first attempt at publication, I'm not sure if I should be worried about it being a sign of the original reviewer realizing the work is unsuitable for the journal and wishing to get another opinion for that reason, or if there's still a good chance of eventual publication. Any similar experiences or opinions on this matter would help.<issue_comment>username_1: I'd take the news at face value: now that the paper has gone through several revisions, the reviewer is unsure about the paper's suitability for that journal. It would have been better if they had predicted that from the beginning, for example, sending you a note along the lines of "after some revisions, this paper might be better suited for another journal", but they didn't. I'd take it as a good sign that they are not rejecting the paper outright. I've never had this happen to me when submitting papers, but it has happened to me as a reviewer, that of being unsure of a paper's suitability after several rounds of revisions. It's a human enterprise.
Upvotes: 1 <issue_comment>username_2: You may have worries, but they may be misplaced. It is the editor's job to decide on suitability, not the reviewer's, though they can make recommendations. Reviewers are responsible for evaluating correctness and originality (novelty).
A more likely situation is that the reviewer suddenly had doubts about the correctness of the paper itself as might be the case in a technical field such as math. The more information that is revealed in the recent edits might cause rethinking of some issue(s).
Yes, you are at risk of rejection, but that is always the case until the editor accepts the paper.
You are free to ask the editor what the concerns might be, though you may not get much of an answer. And it is in your interest that there is a thorough review. It is what it is.
Upvotes: 2
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2023/08/18
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<issue_start>username_0: My partner and I are both in academia - he is a medical fellow and I am a PhD candidate in biology. It looks like I'm going to be defending in about a year or two and he will likely be finishing his fellowship in 2 years. This means that we're going to be in a position where we're looking for long-term positions at the same time. We are not married nor engaged, so I fear that a spousal hire may not be offered if we are only partnered. Of course, in this situation I would be the one that is the spousal hire and not him. Also in this situation we are hoping that he gets funding to impress a university.
How have you all fared with spousal hires specifically in the US and Canada? Or what have you all heard?
Thanks!<issue_comment>username_1: This will depend on the institution's policies. But for most places I've seen, no, you don't have to be married. Most policies will talk about "domestic partnership" instead of marriage. The rules can differ for other issues related to the hire, for example, health insurance.
Upvotes: 3 <issue_comment>username_2: I'd guess that in the US and Canada, any couple could make it known that they are a "package" and require some accommodation if an offer is to be considered. I wouldn't assume, however, that you are the lesser quantity in that package as your skills might be much more valuable to an institution than (gasp) a medical person.
If there is no possibility of considering the package they will let you know and you can look elsewhere. But you have to make it clear. A university has to be convinced that both (each) of you are capable and potential contributors to the overall mission. No one rides for free.
You might also consider looking in places that have several universities and, perhaps find a pair of jobs at nearby institutions. That doesn't necessarily mean NYC or Stanford. Even in my rural location there is a State university and three four liberal arts colleges within an easy commute. Several community colleges as well. And several hospitals, though they aren't research hospitals AFAIK.
Upvotes: 0 <issue_comment>username_3: Obviously it may vary from university to university. But in most cases, if university likes you to join them, they try to make the offer as attractive as they possibly can. I have seen them helping find a job even beyond the university. Usually these terms are not written in stones and have to be negotiated. If a new faculty a university is interested in and said they love the job but can’t move as their partner also needs to find a job. The things they typically do is try all avenues to accommodate the request but nothing is guaranteed (spouse or not)
Upvotes: 2 <issue_comment>username_4: *"How have you all fared with spousal hires specifically in the US and Canada?"*
I fared rather dismally: my (now ex-) wife was in medical profession and I was in mathematics. I had to change the location twice: first time when she finally got a long-term job and second when she lost it in one place and found it in another state. Once I was even seduced by my friend to accept an invitation to be a speaker at the ICM: he claimed that "if I agree, the university would certainly assist me with finding a job for her in the area" (that was when she was looking for a new job after she was told that her contract wouldn't be extended), but nothing of the kind really happened though I honestly went there.
I should say that all places I worked at were very accommodating as far as my own needs were concerned and allowed me long absences and such when we were living in different states with a small daughter (the longest commute was from Michigan to Vermont: an 11 hour drive through Canada one way) and I'm really grateful for that, but as far as finding a job for a spouse, they either could not do anything or weren't willing to and I'm not guessing which one was the case.
A former postdoc of mine was a bit luckier: they hired his wife to one place and himself to another 4 hours (by car) away. They were able to reunite 2 or 3 years later. But they were both mathematicians, so everything could be decided within a single department, which usually makes negotiations much easier.
As far as I see it, formal marriage is not really required in most places in the US, but being in different fields can subject you to all uncertainties of the political relations between different departments (from my perspective biology and medicine are, of course, closer than mathematics and medicine, but they are still not exactly the same thing). I wish you all the luck, but be ready for a bumpy ride at least in the beginning and try to be flexible and consider sacrificing some of your ambitions if you value your relationship.
Everyone's experience is different of course, but you asked and here are my 2 cents :-)
Upvotes: 2 <issue_comment>username_5: You should make the right decision. You will be defending your thesis in 1 or 2 years, that means you have enough time to know your partner more. You are interested in spousal hire, which means you want to be with your partner in the same institution, which means you are likely committed in your relationship, so it is better to take final decision about your relationship when you start at job at same institution. After knowing each other enough, if you are determined about the relationship, then marriage is beneficiary in every way, either in ethicality of professionalism in your future work place or in social perspective. But if you are not sure about your relationship even after 1-2 years, then you should think carefully about joining the same workplace. So at first get out of the complicated zone by deciding something suitable for you.
Regarding your question, it depends on the institution you would want to work with. Certianly there will be less choices if you are not married with your partner compared to the situation when you are married with your partner. People might not flag your relationship status directly but might have hesitation in their mind when hiring you and your partner.
Upvotes: 0
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2023/08/19
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<issue_start>username_0: I wrote a paper that had a similar idea to a paper that a famous professor wrote. I put my paper in arXiv. He put his paper on arXiv after me. I asked him to cite my paper, but he outright refused to do that, even though it was obviously the same idea.
His paper got accepted at a prominent conference, and he is yet to submit a camera-ready copy. My paper was half-baked experiments, not polished and was rejected by the conference, but it had a similar idea and was on arXiv. Shouldn't he cite a paper "he knows of" on the *exact same idea*? What should I do?<issue_comment>username_1: It sometimes (if not frequently) happens that scientific ideas are developed independently from each other. This appears to be the case. Your "famous professor" made a paper of a quality ready to be published and you had "half-baked experiments" and a paper not ready to be published. Since it takes a lot of work to do experiments and write a publication quality paper, it seems that if indeed the idea was the same, that then the "famous professor" had it first. The "famous professor" if pressed might even be pointing to grant submissions containing this idea. Also, not everyone follows arXiv regularly, though that is sub-discipline dependent.
Whether the "famous professor" has a duty to cite you in the related work section depends on a variety of factors. First, is the value of the "famous professor's" work in the idea or in the scientific evaluation? Some ideas are not all that novel, such as using flash memory instead of disks for certain data structures, and the scientific value of research in these ideas is in the details and implementations. Second, is there actually something to cite? Is your arXiv paper in reasonable shape or is it going to still change a lot. From what you tell us it is not clear whether refusing to mention your arXiv paper in the related work section is against academic standards or not.
You seem to feel disrespected. You need to go to someone at your institution whose academic judgment you can trust and have them look at the situation first and see whether an independent observer would agree with you.
But ultimately, there is not a lot to gain from any action. At best, you were working in parallel and while the "famous professor" waited with an arXiv paper until the paper was ready, you rushed a submission. So, you can claim to have had an interesting idea in parallel but were beaten in the race for publication. Unfortunate for you, but not something you can complain about. Not being cited hurts one's ego, but there are no sanctions against that from which one could profit. What would you gain if by some magic you could force the "famous professor" to cite you?
Upvotes: 5 <issue_comment>username_2: Two things: (1) ideas are worth nothing by themselves, and (2) Godzilla sits wherever he wants.
(1) When we say that academics trade in ideas, that ideas are the currency of academics, and that everything starts with an idea, etc. we are using idioms and not talking about how things really work. It's not the idea that matters, and it's not a game of calling dibs on ideas and then living off the residuals. What matters is to be the first one with an idea that is tested, exposed, formalized, explained, and sent in final form to a peer-reviewed journal. A lot of unsuccessful academics go around telling everybody about their ideas, writing them in blogs and otherwise trying to have some record that they were the first one with the idea. This with the misconception that the "only" thing left to do is to formalize, "write up", "button up", test, etc. the idea. Well, the testing and buttoning up *is* what matters, not an afterthought.
(2) One of the benefits of being a famous professor is that you get to publish stuff that others can't. I'm not talking about bad science, although that happens too, but about papers lacking an exhaustive literature review, ideas that others have presented before in better form, and just plain papers that are more like "takes" ([in the parlance of our times](https://www.youtube.com/watch?v=Wbv3gJ76NT8)) than actual research results. It's unfair, maddening, and not how things would work in a meritocracy. But academia is a human enterprise, and we humans like to canonize saints, and well, it is what it is.
Back to your particular case, it seems that the famous professor actually beat you to the punch by writing it up in publishable form before you did. And he has no ethical or otherwise obligation to cede to you what is actually his. But even if your idea was not as half-baked as you say it was, and that the journal should have accepted your manuscript pending revisions, people would probably still cite the famous professor and not you as the originator of the idea.
The episode is not without its share of good news for you: if the idea was indeed a big jump (A -> C) and not merely a follow-up (A.1 -> A.2), it's an indication that both you and the famous professor are thinking along the same lines. It's a good sign of your abilities, so next time, polish your idea and send it off for peer-review.
Upvotes: 5 <issue_comment>username_3: I am guessing you are new to academia, so let me tell you that there can be a really, really big difference between ''having an idea which turns out to be correct'' and ''doing all the work and polishing it to show that it all works out''.
I would go to whoever your academic supervisor is, explain the situation and show them both papers and ask for an honest opinion.
Upvotes: 4 <issue_comment>username_4: Do you have a personal problem with this professor?
I mean you are not asking to put your name in the paper as contributed to the idea, you are talking about citing your work which should be normal and added value to the paper if it gathers all previous related work about the topic; ie, it won't deminish his work
.
-I once got a reviewer comment (who rejected my paper) saying "there is a relevant work missing" without even telling what is the related reference.
-It's also normal nowadays to put blog posts, twitter threads, Bitcointalk.org links in the references; and you're talking about an arXiv accepted paper (they do review papers)
-I can't judge how relevant your work to the professor's paper, but I think the reviewers committee of the publishing conference/journal can if you send them the details (your paper and what you think is the relevance)
-You see what I mean, it is not a fight; if the reviewers believe the authors missed an important relevant reference (think as a paper reader, will you gain added value if you read your paper? even a detailed explanation of a brief point?) they can simply ask the authors to add the reference while preparing the final camera ready version.
-and I don't agree that ideas don't worth anything if not executed, sometimes people buy and sell ideas. Not in research anyway, there are many theoritical papers out there.
.
Final Comment:
This is my opinion but I've seen it twice (not mentioning a very relevant, and executed in code by the way, previous work; I remember tweeting both sides in one tweet). I will not mention the exact papers here because maybe the postgraduate student didn't tell the supervisor professor who thought this the student idea as part of his research.
Upvotes: -1 <issue_comment>username_5: There are several good points to consider in the other answers and comments so far (and there's a bit of overlap between what I write below and what others have already said), but my overall stance on the situation is a bit different.
**0. On ideas.**
Other answers and comments have discussed how much value there is in an idea alone. I think it might be worthwhile to mention more explicitly that there are various different things described by the word "idea". For instance,
* an idea to investigate a certain question;
* an idea regarding which methods one can be used to answer a given question;
* more concrete ideas on how to implement a certain step or to solve a certain subproblem;
* in mathematics and related theoretical fields there are also situations (which might be a bit unique compared to more experimental fields) where an "idea" can be a deep insight regarding a certain construction or argument that can be used to prove a theorem or to solve an open question. In some cases it can happen that once you see the idea, this does indeed essentially solve the problem, with the technical details remaining a "formality" that you know will work out anyway. However, this situation is far from universal in math and moreover, it requires quite some experience and intuition to see whether this is the case when one just see the idea.
I agree with others that in many situations much of the effort is not in having an idea, but in developing and testing all the details (or doing all the experiments in experimental fields). Even in very theoretical fields like math this is often true, in particular when one is not talking about very concrete proof ideas or arguments but rather about ideas on "which questions to ask" or "which object to define and study" or "which theory to develop".
**1. What behaviour by the famous professor would be most appropriate academically?**
As others have said, it is impossible to give a definite assessment without knowing all the relevant details - in particular how vague or concrete your idea is worded in your arXiv preprint or how innovative or novel your idea really is compared to what can already be found in the literature.
However, despite what I said in point 0., I tend to come to a different conclusion than some of the others answers and comments:
Even if the idea alone does not represent the majority of the effort or insight and even if the rest of your paper was rather half-baked (and possibly even if the idea itself was not as well developed by you as it could or should have been), I'm inclined to say that the most appropriate course of action would still be to cite your preprint (not matter whether the other paper might have been in a more final state and might be published earlier).
The main reasons are:
* It is in the interest of the reader to find sufficient context in a paper. Another paper or preprint which uses a similar idea seems to be relevant context (unless the idea is very much common place in the field). For this reason, I would personally even tend to add a citation during a revision of my paper if a relevant preprint was uploaded only after my own paper was uploaded to arXiv and submitted to a journal.
* The other point of citations is, of course, about credit and priority. Admittedly, I don't really follow the arguments in some of the comments that one wouldn't need to give credit to your idea if the idea alone establishes only a small part of the novelty or insight in the famous professor's paper.
When I write a paper which, in any way, uses an insight or idea that is not already common in my field, and which has been brought up by someone else before me, I will certainly cite it (even if I came up with the idea myself before knowing about the same idea of the other person). I don't see any reason why this should only apply to ideas or insights which have a major impact on my own paper or constitute a significant part of the scientific effort that went into developing the paper.
If I have a perfectly valid proof of my main theorem and I find out the proof of my auxiliary Lemma 7.3(ii) can be simplified a bit by using a concept recently introduced in a preprint by a colleague, I'm going to cite them. If somebody else defined the same notion as I did but earlier, and their presentation is messier than mine and their results are much simpler and not deep at all, I'm going to cite them. If somebody proved a very special case of my theorem with a more complicated and less insightful proof I'm going to cite them.
All of this also applies if I learn of the earlier work only after I have already completed my preprint. To be completely honest, not citing the other person in any of those cases would seem rather conceited and, frankly, a bit pigheaded to me. And it would be in contradiction to the goal to contribute to the advancement of the scientific community I'm working in.
**2. Why might the famous professor refuse to cite you?**
That's of course impossible to answer without much more information. All we can do is speculate. Here are a couple a various potential reasons. Let me say very clearly that I am making not claim whatsoever that some or any of those potential reasons apply in your specific situation. I'm just trying to offer you a broad perspective on what could have happened.
* The famous professor might have genuinely considered your message and finds, on purely academic grounds, that your contribution in the preprint doesn't warrant citation. For instance, they might disagree with your assessment that the idea is exactly the same and rather believe that it so distant from their idea that a citation doesn't make sense and would rather confuse their readers. Or they might find that your idea is worded so vaguely and generically that the idea itself doesn't really count as a scientific contribution on its own. Or they might consider your (and their idea) so common place that all the contribution is really in the details with the idea itself being widely used in all sorts of similar contexts.
Please note that I'm not saying whether or not such an assessment would be correct. I have no way of knowing this. Please also note that even if an author claims that an idea is "exactly the same", this does not necessarily mean that everybody else comes to the same conclusion. Similarity (or identity) of ideas or the question what precisely is an insight and what is, on the other hand, trivial, depend very much an personal opinions.
* The famous professor might be disorganized and thus have forgotten to respond to your request. (If however the professor replied to you and explicitly said that they are not going to cite you, this explanation is ruled out, of course.)
* It might be that the famous professor really just doesn't give a damn about whether or not to cite you and doesn't want to take the effort to include the citation. Yes, sure, it's not that much effort at all - but just as other human beings, professors (famous or not) don't always act rationally.
* Maybe the famous professor is a conceited and pigheaded jerk and thus doesn't want to share any credit with you. Yes, there are famous professors who are conceited and pigheaded - just as there are famous professors who are very well-meaning, modest, and extremely generous with giving credit.
* One more potential explanation, which you might not like very much:
Please be assured that it is not my intention to offend you - but from the wording of your question and various of your comments, one can get the impression that you might sometimes appear a bit confrontational and, also, entitled. Communicating in such a way makes it much less likely that you achieve what you would like to achieve, in particular if you are asking someone else for a certain action. Please let me point out to important issues related to this:
a) What I said above is not directly related to whether or not you are right. If others find that you appear confrontational or entitled, this will likely not lead to the outcome that you desire, even if you are, from a neutral point of view, completely right with your request. Thus, in most cases it is a good idea to remain polite and modest in your language, even if you have very strong feelings about something.
b) As an illustration: I'm also a bit under the impression that they way you worded your question and your responses in a number of comments contributed to the - from my point of view - somewhat one-sided perspectives that you received. On Academia StackExchange there are a variety of questions on citation and the attribution of academic credit, and some of the responses to those questions tend to rather lean on the "one should be very generous with giving credit" side. However, when people get the impression that you might not be asking in completely good faith (even if you actually are and this is just a communicational issue), it is likely that they will be somewhat biased to argue against your position.
**3. What course of action is best for you?**
Here are a few general suggestions, based on what I said above and on what others have said:
* When you are under the impression that your publicly available work is relevant to the work of other people but those people did not cite it, I think it is, generally speaking, ok to inform those people of your work.
However, the way how you do this is extremely important. I strongly suggest to write such a message in an extremely polite way. But also be concise whenever possible. For instance, do not spend lengthy paragraphs on philosophical thoughts that might appear defensive or passive-aggressive: don't write something along the lines of "You do, of course, have no obligation at all to cite my work and can completely decide on your own whether you consider my contributions sufficiently relevant to be cited in your important work". Leave out any such philosophical thoughts and stick very much to the contents you are referring to.
Under any circumstances, make sure not to sound confrontational or entitled in such a message. Do not request the other party to cite your work and do not imply that you expect them to cite it, even if you strongly believe that they are somehow obliged to do so. Keep it all within the frame of "this seems to be related to your work, so I send it to you in case that this might be interesting for you". Being more concrete will likely be received more positively (unless you overdo it and appear to be nitpicky). For instance, saying "the approach that you use to do XYZ on pages 16-18 seems close in spirit to the approach that I used on pages 21-24 to do ABC" is likely to be more helpful than just saying that "our papers seems to use related ideas.
Please note that none of this is guaranteed to lead to a positive reaction. But if you choose to write such a message, the more clear and modest your message is, the more likely a positive reaction becomes.
* Even then, don't do this too often and even less so to the same people. Even if you're right each time - if you find that a certain group of people will just continuously ignore your related work in each new article, then you'll quickly reach a point where it's the wisest course of action to just let it go.
* Similarly, if somebody comes to a different conclusion than you and chooses not to cite your work despite you having showed it to them - I strongly advise against trying to force it in some. After all, you usually don't have much leverage and the only thing you'll achieve is to get people upset. If you find this unfair and frustrating, you have my sympathies - a lot of things in academia actually *are* unfair and frustrating. But as for all things that you'd like to see changed but are hard or almost impossible for you to change, it is wise to ask yourself if this is really the hill you want to die on.
* One more thing: I've experienced situations where, say, a colleague A was angry about a colleague B not citing them on various occasions, even though a citation might have been warranted. Then A decided, in turn, not to cite related work of B anymore, even of the mentioning of the related work of B would have likely been beneficial to A's readers.
Please let me advise against any such retaliation practices. Admittedly, it is a very human instinct to do this, but in the setting we are discussing here it simply won't do you any good (on the other hand, it might or might not hurt you, either). Reacting to unprofessional behaviour by behaving unprofessionally yourself is unlikely to make you feel better in the long run and it is certainly not a winning strategy (although one can easily find examples of successful people who fight their share of vendettas - for me, the most reasonable perspective on this is that those people are successful despite their vendettas, not because of them).
Upvotes: 4 <issue_comment>username_6: The only basis for *compelling* the famous professor to acknowlege your own prior work in this particular area is if you can **prove he had made no progress on this matter until after your own paper was published in Arxiv.**
This would be hard to do. You might convince yourself and perhaps many of us that the development of this idea as presented in the professor's paper is totally implausible, scientifically and humanly. But it would not make it the impossibility demanded before the scientific community would reject the famous professor as a co-originator.
It's always possible for 2 scientists to independently arrive at the same concept. In such situations, each originator can publish their *first* paper on the idea without reference to the other. But all subsequent papers would need to acknowlege the work of the other regardless of evaluating it or not.
I would advise against any further pressing of the other professor on this matter. He may well be cuckooing your nest. But if he is - and I say, "if" - he seems to be better at cuckooing than you are at catching him.
Upvotes: 3 <issue_comment>username_7: To take a very stark [bibliometric](https://en.wikipedia.org/wiki/Bibliometrics), long-term view, there is only one difference between a scenario where the professor accepts your priority and one where he doesn't (with no consideration of it being the "right thing to do").
If he accepts your priority, your arXiv preprint gets one citation.
If he doesn't accept your priority, your arXiv preprint doesn't.
That's it.
Unless you've both discovered something as earth-shaking as [CRISPR genome editing](https://www.science.org/content/article/latest-round-crispr-patent-battle-has-apparent-victor-fight-continues), "priority" plays little role in determining how far and wide one paper spreads compared to another. Unfairly, papers get cited based on who wrote them, whether reviewers force new papers to cite them, and so on. Those factors you can't control.
Fairly, papers also get cited more if they are clear; if they are persuasive; if they are robust about their strong results (and gentle about the weaker ones); if they outline imaginative implications and future avenues of research; if they are easily replicated and extended. Those factors matter far more than whether or not their arXiv preprint was cited zero or one times.
Therefore, what you should do is prioritize writing your preprint up into a good, solid paper. Let your work's quality speak and win citations for itself, and do your networking to let future potential citers and collaborators know what you've done!
Upvotes: 3
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2023/08/19
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<issue_start>username_0: I'm currently writing my MSc dissertation for an MSc in Artificial Intelligence. My university allocates a 3-month period for the whole project.
At this point in the project, I realised my reasoning behind the model is somewhat flawed, but that is not a valid reason to request an extension. I am stuck in a loop of writing and re-writing my observations, but I can't seem to make any progress as I keep re-writing the same portions of the dissertation.
How should I approach writing the dissertation, given my reasoning was somewhat flawed from the start and I have no way of changing/re-implementing the model?
EDIT: I have spoken to my advisor, but as he is one of the two people marking my work, he can't really give me guidance on the topic outside of "explain your reasoning". I realised the issue quite recently and he said he would be unavailable until a couple of days before the deadline, so I can't currently contact him regarding my issues.<issue_comment>username_1: Assuming that you don't have the time anymore to change and correct things, you could explain the model and your reasoning that led to it, flawed or not, and then you do a Section "Critical Discussion" where you state arguments against it, and how you think it should be changed, and then you declare this as "future work".
Note that generally formal models are never perfect and can always be criticised, and one can find surprisingly bad flaws even in some publications. Of course some issues are more serious than others, but still, in my view, if an MSc student realises at some point that their model approach is flawed and the thesis shows that they understand this now and what the problem is, even without redoing things I'd think that's a good thing. Obviously it may depend a bit on how bad the problem is and whether I'd have expected the student to realise this earlier. But then as a supervisor I could see it as my own job to warn you in time about this, and if I didn't, I may have missed this myself, and so I can't blame you that much (even though I may not have taken that much time to think about it).
I can't know about the MSc thesis marking culture in your place, but as a supervisor I know that the time for doing an MSc project is very limited. It may well happen that a student goes for some time in a wrong direction, and time may not be enough to fix it even if eventually understood. So expectations are limited, and for me as a thesis marker it wouldn't be a big problem. (Of course it may depend a bit on what your ambitions are as it may cost you a few percent, but I wouldn't expect it to break anyone's neck.)
It's the scientific process that we try to solve a problem, go wrong, and then understand things better by learning from our mistakes.
Upvotes: 6 [selected_answer]<issue_comment>username_2: This is an MSc memoir, a compulsory step to your diploma (at least here in France, and generally in Europe).
Nobody cares about the MSc memoir and it is unlikely someone will read it if it is not really interesting.
Yours, according to you is not interesting because the idea is flawed. Your best approach is to say so and explain why it is flawed. And be done.
Your supervisor thinks the same so do not worry about writing a masterpiece.
There are thousands of MSc memoirs that have zero useful content, and they are still on the right side of the face, compared to those where there are lies added. Do not lie or hide anything - this is something that is not only immoral (YMMV) but also potentially a risk for you.
Upvotes: 2
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2023/08/19
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<issue_start>username_0: I am a PhD student at a University that isn't top rated in my field, and have only published once before and wasn't even cited. I want to submit what I believe is a really great paper to the top conference in my field. Will my paper be judged only on its merits? Or will my lack of credentials prevent reviewers taking it as seriously as someone with a high h-index at a prestigious University?<issue_comment>username_1: I don't know your field, but in mine (CS) the paper will get a fair reading and accepted or not on its merits.
There is a lot of competition, of course, and a limited number of slots for presentation so nothing is automatic. But my experience is one of acceptance and a desire to push the boundaries of knowledge and practice, not to assume that everything good comes from Harvard.
And use the time at the conference to build yourself a circle of contacts who can eventually become collaborators.
There are lots of great people working at universities that don't have great names. Don't be intimidated.
Upvotes: 3 <issue_comment>username_2: First, in my field, some top conferences have a double blind reviewing process. Second, the large number of competent researchers and limited positions at top 100 institutions mean many of these researchers are now located beyond the top 100 universities. Third, it is easier than before to access information and become a competent researcher. For these reasons, a high quality paper with a good idea can come from almost anywhere.
Having said that, the key problem with lower rank institutions is that they may not have the people or/and resources to carry out high quality research. I have reviewed many papers from these institutions, and many authors simply do not have the processes to carry out high quality research nor know what is high quality research.
Whether your paper has a chance will very much depend on your supervisor(s). Does he/she have a high track record of publishing high quality work? If not, even if your idea is great, it may lack many key ingredients expected by your community. This means it is not the 'brand' of your institution that matters, but the quality of your work.
Upvotes: 0 <issue_comment>username_3: It depends solely on the conference. In machine learning conferences, papers are typically reviewed in a double-blind fashion. While the existence of a *preprint* might pose an unfavourable advantage for 'big names,' your paper will still be reviewed based on its merits, and **no one will take your previous publication record into account,** at least not in a negative fashion.
Good luck with your submission!
Upvotes: 0
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2023/08/20
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<issue_start>username_0: I graduated from a U.S university one year ago. If one year after my graduation a person or a group of persons claim(s) to the university that I harassed them (verbally or physically), could this claim lead to the revoking of my degree?<issue_comment>username_1: Universities and colleges are governed by their own rules. I would be surprised if a degree revocation would be possible based on bad behavior alone, even if the bad behavior would be criminal. Bad behavior is usually sanctioned in other ways such as expulsion or suspension, or by going through the criminal or civil justice system. After graduation, the institution itself is usually not in a position to sanction the now ex-student in a meaningful way. They could kick the ex-student out of the alumni association and send a letter of reprimand, maybe. Redress for a victim would need to go through the criminal or civil court system.
Degree revocation usually needs to be based on some type of grievous *academic* misconduct, such as repeated cheating on examinations or serious plagiarism in a thesis.
However, without knowing your institution and the rules of that institution, nobody here can answer this question.
Upvotes: 2 <issue_comment>username_2: People can claim whatever they want, and a claim by itself should be no basis for disciplinary action. Now, if their claim is substantiated with evidence, the consequences will depend on the severity of your actions. "Verbal or physical harassment" (your words) covers a wide range of behavior, from saying something others don't like, to stalking (I don't really know what other behaviors could be incldued under "physical harassment": if you physically touched people, that'd be assault.) It is unlikely to result in the revocation of a degree at any university I know of. But there might still be consequences if the act was illegal, e.g. if you stalked, you might still get a restraining order issued against you, etc.
Upvotes: 2
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2023/08/20
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<issue_start>username_0: The Arecibo observatory [shuts down](https://www.scientificamerican.com/article/closing-down-an-icon-will-arecibo-observatory-ever-do-science-again1/) its science.
This looks like the last step in its long decline caused by gradually reducing funding over time: the huge legendary radio telescope cannot be properly maintained, it collapses, there is no money to repair it, and it now, finally, reached its end (there are still other, yet smaller telescopes remaining.). There was a time when there was money to build the telescope. Why did this change so much?
The legitimate explanation would be that this radiotelescope was no longer scientifically interesting, or at least less than when it was built. Or was it a defense project that lost its military significance? Or just palace intrigues over funding? Or something else?<issue_comment>username_1: >
> it collapses, no money to repair
>
>
>
The simple answer is that the 2020 collapse was irreparable. Much of the telescope was destroyed and would have had to be completely rebuilt. Spending so much to rebuild a 60 year old telescope does not represent a good value proposition. It is true that an updated, modern telescope at the same site has since been proposed, and rebuilding at the same site would offer cost savings and cultural benefits. However, this proposal's price tag still comes to a $400 M, so the odds of funding seem remote.
The more interesting question is perhaps: why wasn't avoiding this collapse more of a priority? The NSF drastically cut funding to Arecibo in 2007 and was already planning a "controlled demolition" rather than a costly repair in 2020, when the telescope was in danger but hadn't yet collapsed.
To me, the official explanation is plausible. Astronomy budgets in the US are always tight. Arecibo was built in 1963, and while it remained relevant 45 years later (in 2007), it also remained costly. And by 2020, the value proposition was even worse: if NSF had only tepid interest in funding the observatory when it was fully functional, it's unsurprising that they would not be interested in funding costly repairs fifteen years later.
Upvotes: 3 <issue_comment>username_2: When Arecibo was built it was the largest radio telescope. There is now the larger filled aperture system in [China](https://en.wikipedia.org/wiki/Five-hundred-meter_Aperture_Spherical_Telescope) and several very large [array](https://en.wikipedia.org/wiki/Square_Kilometre_Array) [telescopes](https://en.wikipedia.org/wiki/RATAN-600).
As such rebuilding Arecibo as it was would be a lot of money to be 'somewhere in the top 10', which is a hard sell politically.
It is possibly also relevant that radio telescopes built into terrain can only point at a very small volume of space because they are rather immobile, this means that Arecibo has scanned all the sky it can see from that location to the precision the system allowed, and the China 500 meter array has similar sky coverage (18 vs 25 degrees north) and is generally more capable. The loss of Arecibo does impact [high power](https://en.wikipedia.org/wiki/Five-hundred-meter_Aperture_Spherical_Telescope#Comparison_with_Arecibo_Telescope) active radio astronomy, but most of the bodies of interest now have orbiting radar equipped space probes.
If building a similar capability doing so in the southern hemisphere would probably offer the highest science per $ return as the skies would 'new' for this type of study, rather than trying to fit a larger/more capable system into the Arecibo geography.
Upvotes: 6 [selected_answer]<issue_comment>username_3: Arecibo was funded by DoD, NSF, and NASA.
DoD lost interest in 1969.
From 1998 to 2020, NASA's budget increased from $25.48 billion to $25.51 billion in 2022 dollars. The cost of the Webb telescope increased from $1.83 billion to $9.66 billion in 2022 dollars.
LIGO cost over a billion dollars. Over the lifetime of LIGO, NSF's inflation-adjusted budget decreased by over a billion dollars per year. Astronomy gets a small slice of NSF's budget, which is smaller than NASA's budget.
A lot of stuff got cancelled.
Upvotes: 4 <issue_comment>username_3: A bit of a contrarian answer: Arecibo's funding lasted much longer than normal. Arecibo is older than Voyager, Green Bank, Hubble, Keck, Mauna Kea ...
Lovell and Haystack are the only major facilities I can think of that are older than Arecibo.
Arecibo lost funding because it reached the end of an exceptional streak of funding successes.
Upvotes: 4 <issue_comment>username_4: Because the whole one mega project solution mindset is pretty outdated? Today you take software, several small distributed radio telescopes with excellent time measurements and combine them into one huge virtual telescope the size of the planet.
Upvotes: 0
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<issue_start>username_0: I wrote to a professor at a German research institute who was hiring PhD students. His area was a bit different from mine, but he wanted to have a chat. We met over Zoom and I told him about my projects. He found it impressive and said he wanted to explore supervising me and would get one of his colleagues to cosupervise given the minute differences in areas of research. He also asked me to prepare a technical presentation and requested the names and contact details of my references.
After preparing my presentation I emailed him. He was at a conference but still listened to my presentation and asked a lot of questions, took a lot of notes. The presentation was based on a paper he wrote. I could answer most of the questions apart from one. He also told me that he has written to my referees for the references and has even discussed ideas about co-supervison. He said he would also assess the presentation and discuss it further with his colleague and will be in touch.
My referees sent the reference letters. One of them was delaying it and wrote to him saying he’ll take time to which he asked to write at his own pace. But since our last interview he never wrote back to me. It’s been 11 days. The references have all been sent.
His automatic reply says he’s travelling and will be slow to respond but nevertheless he replied to my referee and not to me. I wrote to him that my first referee has furnished the letter while the 2nd individual may take time.
Can anyone tell me if this looks negative or positive? Is the professor avoiding me, in which case it would be safe to assume that he is not interested.<issue_comment>username_1: It will only be safe to assume he isn't interested when he says so. Quite the opposite, he seems to be still interested, though very busy.
If he doesn't want to follow up he will likely say so and then you will know. Good luck.
I don't know if his being busy is a warning sign, though, for future guidance. Keep that in mind as you proceed. But this is the season to be busy with professional things for researchers, so maybe not an issue.
Upvotes: 3 [selected_answer]<issue_comment>username_2: People in Germany take their summer vacation seriously. Some nevertheless look into their email every once in a while and may chose to answer select mails that they deem important. He sought it important enough to answer the referee to assure them a delay won't matter and prevent stress for them.
If the professor is on vacation and needs to discuss your position further with a colleague he can only do this when back from vacation. Of course it is not ideal for you, but there is really nothing you can do but wait. Normally there is a date given in automated messages that tells you when the person is supposed to be back im office. Give him a few days after that to catch up with things and then contact him again.
Upvotes: 2
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2023/08/21
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<issue_start>username_0: Background information (you can skip this)
==========================================
There's a technology called automatic textbook billing, or "inclusive" access (IA). It is also known by [many other names](https://www.inclusiveaccess.org/resources/faq#:%7E:text=How%20do%20I,and%20Immediate%20Access.).
With IA, students are generally billed automatically for e-textbooks, unless they opt out.
### Disadvantages of IA
There are many issues with IA, including [cost](https://www.inclusiveaccess.org/facts/savings-or-spin#:%7E:text=Compared%20to%20used%20books%20and%20print%20rentals%2C%20Inclusive%20Access%20can%20actually%20cost%20more%2C%20and%20there%E2%80%99s%20no%20way%20to%20share%20or%20borrow%20copies.%20Inclusive%20Access%20may%20save%20money%20for%20students%20who%20normally%20buy%20new%20print%20textbooks%2C%20but%20it%20can%20cost%20other%20students%20more.), [format](https://newrepublic.com/article/120765/naomi-barons-words-onscreen-fate-reading-digital-world), [expiry](https://www.inclusiveaccess.org/facts/retain-or-just-rent), and [other issues](https://www.inclusiveaccess.org/).
Instead of using IA, faculty can adopt free online Open Educational Resource (OER) textbooks. OERs are cheaper. Also, unlike IA, OERs may improve academic outcomes. [(Source.)](https://www.inclusiveaccess.org/facts/solution-or-status-quo#:%7E:text=In%20contrast%20to%20Inclusive%20Access%2C%20the%20use%20of%20OER%20has%20been%20extensively%20studied%20in%20the%20research%20literature.%20While%20many%20studies%20do%20show%20improved%20academic%20outcomes%2C%20neutral%20results%20are%20still%20viewed%20as%20positive.%20Why%3F%20OER%20replaces%20traditional%20paid%20materials%20with%20sustainably%20free%20and%20open%20ones.) Sadly, many faculty don't know much about OERs. [(PDF source.)](https://www.bayviewanalytics.com/reports/turningpointdigitalcurricula.pdf#page=5)
### Advantages of IA
IA increases publishers' revenues. This lets them produce slides, videos, test banks, and more. It also lets them produce textbooks which are far more polished than free online Open Educational Resource (OER) textbooks.
My question
===========
IA textbooks normally self-destruct after a year or so. [(Source.)](https://www.inclusiveaccess.org/facts/retain-or-just-rent) This can cause problems for students. [(Example.)](https://openstax.org/blog/if-inclusive-access-horizon-ask-yourself-these-nine-questions#:%7E:text=Does%20the%20inclusive%20access%20program%20provide,she%20only%20had%20a%20limited%20subscription.)
Perhaps it might be in textbook publishers' best interest to offer students extended access to their IA textbooks, longer than one year. Publishers could offer this either for no additional cost, or for an additional fee.
Long-term access might make students and instructors happier, at little or no cost to the publisher. And it might invalidate at least one common criticism of IA.
Traditional e-textbook **retailers** often do offer customers a choice between rental or perpetual purchase. [(Example.)](https://www.vitalsource.com/products/psychology-david-g-myers-c-nathan-v9781319347970) The perpetual purchase option may cost more, but at least it's possible.
But I'm not aware of any **IA providers** which offer long-term access as part of their IA programs. Why not?
Related
=======
* [Why don't " 'inclusive' access" textbook publishers find a way to prevent resale, without requiring automatic textbook self-destruction after a year?](https://academia.stackexchange.com/questions/200918/why-dont-inclusive-access-textbook-publishers-find-a-way-to-prevent-resale)
* [Is it ethical for a lecturer to require students to purchase an online learning kit where kit is used for course assessments?](https://academia.stackexchange.com/questions/18190/is-it-ethical-for-a-lecturer-to-require-students-to-purchase-an-online-learning)<issue_comment>username_1: [Rent seeking.](https://www.investopedia.com/terms/r/rentseeking.asp) Replacing durable goods with artificially consumable goods is very common because it is profitable. Every industry that can is switching to a software-as-a-service model because they think that is where the money is.
[Planned obsolescence](https://en.wikipedia.org/wiki/Planned_obsolescence) is a long-standing practice in the textbook business. Publishers used to renumber homework problems to make old books obsolete. Deactivating digital books is a new version of the same thing.
Upvotes: 6 <issue_comment>username_2: >
> But I'm not aware of any IA providers which offer long-term access as part of their IA programs. Why not?
>
>
>
Apparently because they have found this not to be in their best interest. Companies are not in it to make customers happy: they are in it to make money. Happiness of customers is only a consideration towards an end. So, one might speculate that textbook companies have done market research showing that offering long-term access:
1. Would not bring in substantial additional profit.
2. Might undermine the market for students who, for some reason, currently purchase short-term access multiple times.
3. Would not prevent students from switching to competitors.
Upvotes: 6 [selected_answer]<issue_comment>username_3: Does [this example](https://www.ohiolink.edu/sites/default/files/uploads/2022_inclusive%20access%20primer_v2.pdf) rejects your hypothesis?
>
> **How long will students be able to keep their e-textbooks in this model?**
>
>
> Students receive perpetual or long-term access under this
> agreement. All publishers have agreed that e-textbooks acquired in
> this model will be available to students after their course ends. A
> student who transfers from one Ohio institution to another will keep
> access to textbooks acquired at their first institution, and for
> publisher platforms with a digital bookshelf, access will be granted
> via a student’s username and password. Students can also download
> e-textbooks to their digital devices and store them locally
>
>
>
>
> **Which publishers are currently participating?**
>
>
> As of today, OhioLINK has agreements with McGraw-Hill Education, Pearson, Cengage
> and SAGE Publishing
>
>
>
I think it is fair eternal online hosting is not included in a discounted price.
On the other hand, you should expect that your students can save a permanent copy (PDF) of the textbook along with any notes.
No reason not to negotiate that, and obviously it was possible for Ohiolink.
Upvotes: 1
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<issue_start>username_0: I recently published at a prestigious conference and I am a solo author. I also do not affiliate to any company or university at the time or during the writing of the paper(I will start my PhD in Fall). What should I write under my name in the camera-ready copy? Currently, I have "Independent Researcher". Is it fine?<issue_comment>username_1: Yes, *Independent Researcher* is fine and recognized. If asked for an email as well, try to use one that you know will last, hopefully forever. (Impossible to guarantee, of course.)
Upvotes: 2 <issue_comment>username_2: If the research was done while you still were at another University, you can site that affiliation - even if you are not working/studying there anymore. This could be also explicitly mentioned in the paper (like a footnote that *The research was done while working at...*)
People also cite their companies or other actual workplace - this may include one's own company, if one functions as a freelancer (in many western countries freelancing legally actually implies an existence of a registered company.)
The problem with writing *Independent Researcher* is that no one knows what exactly is meant by this words - one could just as well write a *Cat Lover* or anything of the kind (no offense intended.)
Upvotes: 1
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2023/08/21
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<issue_start>username_0: I received an article for review from a journal I did not review for before and honestly haven't even heard of so far. It is not a predatory journal, just a journal that until quite recently had a very narrow scope that did not overlap at all with my field of research. The article I was sent to review was within my expertise, though.
To get to know the journal I had a look on their website and from what it seems they recently expandend their scope to a more broader range of topics. Yet in my opinion, the article (which would have been totally out of scope previously) still did not really fit into the new scope either. This is why I wonder: Is it rude to tell the editor that I do not think the article is within the scope of their journal, because sorting out off-topic articles is their job and that would kind of critisize their work?<issue_comment>username_1: I don't think it's rude as long as you communicate it non-rudely. It would be rude for the editor to expect you to blindly review a paper without paying attention to this sort of thing. For example, you could be concerned that you spend time on a review that is ultimately not used because other reviewers point out the scope mismatch and the editor chooses to reject on those grounds.
I think it's fine to say what you've said here: you were surprised at the identity of the journal relative to the content, you checked to see the journal's scope and it seemed to be outside of it. I would also include your decision to review the paper: if the editor assures you the paper will be considered in-scope, are you then willing to review? Are you not willing to review no matter what?
Upvotes: 6 [selected_answer]<issue_comment>username_2: I have written several reviews where I said the manuscript topic did not fit the journal. I do not think it is rude. In my experience the editors ignore this.
If somebody submitted a manuscript to the wrong journal, they might have done it because the editor asked them to. It is also possible that you were asked to review the manuscript before it was viewed by an editor.
Upvotes: 4 <issue_comment>username_3: I don't think it's rude, if you couch it politely and make clear you know it's really their job. Maybe something like:
"Even though I'm just reviewing this article, I wonder if it is truly appropriate for your journal."
And then go on to your review.
Upvotes: 2 <issue_comment>username_4: As an editor, I would not be offended if a reviewer says a paper is out of scope. Having said that, a journal may have their own set of topics that are not reflected officially on the journal's web-site.
As a reviewer, I have stated many times that a paper is out of scope, or request authors to link their paper to topics of interest.
As a reviewer, simply provide information as you see fit. Let the editor decide what is relevant or irrelevant. Above all, just write your comments professionally.
Upvotes: 3 <issue_comment>username_5: It is not rude, but in order to say it is out of scope (which is a reason for rejection) you would have to be very sure that this is the case. If a journal is in the process of changing their scope, I think it is difficult to know for sure where they are heading to.
However, as a reviewer, you will have to state an opinion on whether the paper is written clearly and accessibly, and that depends on the audience, too. So you could give your judgement in terms of what sort of previous knowledge readers would need. Then the editor can make a decision whether this is the intended readership or not.
Upvotes: 3 <issue_comment>username_6: To add onto username_2’s answer: I have previously submitted a paper, which the editor sent to two reviewers. Both reviews were generally positive but Reviewer 2 mentioned they weren’t sure whether the submission fully fit the journal’s scope. The editor commented that they were inclined to agree and suggested submitting to a sister journal.
For us, this obviously amounted to a rejection (and our work was later published elsewhere albeit not in the suggested sister journal). The anecdote does show that:
* reviewers do that
* editors consider that
* and sometimes editors agree after peer review.
Upvotes: 3 <issue_comment>username_7: I would add that almost every journal I have reviewed for has specific questions or check lists in which you are tasked to assess whether the paper fulfills the criteria to be considered 'in scope' for the journal. So no, it is not rude, it's part of normal reviewing.
Upvotes: 2 <issue_comment>username_8: The journals I review for mostly explicitly ask whether the paper is appropriate for the journal.
But in any case, it's not rude to give an opinion on the suitability of a submission having explicitly been asked to do so, which is exactly what it means to review a paper. The editor is then free to use your advice as they see fit.
If you're worried about sounding rude to the author the put it in the confidential comments to the editor.
Upvotes: 2 <issue_comment>username_9: I would not comment on the scope unless asked explicitly by the editor. I think it is the editors job to determine the scope. I would weight the right of the author to obtain a timely review quite high.
Upvotes: 0
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2023/08/21
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<issue_start>username_0: For the next semester, I'd like to give students a reflection exercise after their first assignment -- specifically to confirm that they can access the feedback I leave in the online homework system. However, it seems like a blocker in the case of students who simply skip the initial assignment. What are the best options for handling this kind of situation?
A little more detail: I give programming (sometimes math) assignments weekly, collected and graded via our online learning management system. There's an online rubric attached to each assignment, with gradations checked off in several categories, as well as custom-written feedback from myself to each student. How to access this feedback is presented both in class and via handouts.
Unfortunately, it's nonetheless commonplace in the last few weeks of any semester for one or more students to interact with me and wind up saying, "oh, I never knew there was feedback on the assignments" (so apparently it's been a waste of time for me to do it). My thought for the upcoming semester is to have a reflection exercise immediately after the first assignment in which students access the feedback, prove that to me, and make some improvement based on that. But what should be done if a student skips the initial assignment, such that there isn't any grade or feedback in the first place?<issue_comment>username_1: ### Suggestion 1
* Have them perform the exercise with a submission and feedback that you provide. Since you are not doing this for the first time, you probably have some previous submissions that you can anonymise for this purpose. Ideally, the feedback system allows you to give feedback on a non-submission, so your students still train using the system. Of course, working in feedback on a submission that is not your own is more difficult, therefore:
* Announce beforehand which assignment will be subject to the reflection exercise and what that entails. Recommend to prioritise submitting this assignment as the reflection exercise will be more difficult otherwise.
### Suggestion 2
Make the reflection exercise such that it can be done at any time with any assignment (although there is a default assignment for it). Thus, as soon as a student submits any assignment, they can do the reflection exercise in the next week. It’s not as if they could copy their solution to the reflection exercise from somebody else or benefit from a group discussion, so the normal reasons for having exercises simultaneously are absent.
Of course, depending on how you grade the inflection exercise and how crucial the choice of the reflected assignment is, this may be more work for you.
Upvotes: 2 <issue_comment>username_2: I'd keep it very simple: if a student didn't do the first assignment, then they won't be able to do the reflection either, and so they will get zero points for both of them.
If you want to make it less harsh, you could allow the first assignment to be turned in late (possibly with some deduction of points). When a student notices that they got zero points for the reflection, this might motivate them to go back and complete the original assignment. You could then allow them to complete the reflection after receiving feedback.
In all cases, the students should be informed of the policy, and of the existence of the reflection assignment, in advance.
Upvotes: 3 <issue_comment>username_3: If you're up for an interesting but non-traditional idea --
Obviously, making sure students can see and understand their feedback is very critical, and worth spending some time doing.
In the past, I've given a really short quiz on things that appear in the syllabus to get students to read the syllabus. I thought it was fairly effective. I recommend trying something similar here -- but it might be a bit tricky to instantiate it within your LMS.
Here's how I would do it using tools available to me in blackboard. First, I would create a group assignment. The members of the group would include you and the whole class. Then, I would create a zero-credit group assignment. This whole scheme would rely upon the instructor being able to submit that assignment (left for you to verify). If that doesn't allow you to submit, you would need to create a permanent test user using the student preview tools, and not delete it upon leaving preview mode.
Then, you would simply submit some nonsense to the assignment. Since it's a group assignment, every student should be able to see it. "Grade" it and leave a few comments. Then, give a quiz asking what the comments are.
Upvotes: 1 <issue_comment>username_4: Canvas (I don't know about other LMSes) allows you to lock things until something is done.
So you have the first intro assignment, which doing it unlocks a module with only the reflection, which doing that unlocks the next class module, after which everything else is hidden behind.
Upvotes: 2 <issue_comment>username_5: I think this is such a common problem; it becomes a real disincentive for giving feedback. You are right that there are students who never figure this out as opposed to not being interested.
You don't say what LMS you are using, but in Blackboard you can manually submit the assignment and give a grade of 0. Then you can give feedback on that. Then do the reflection assignment.
One thing is you could encourage students to install the LMS app on their phones and have them view the feedback during class time. That might also help the confused because they can see what their neighbors are doing.
Upvotes: 2 [selected_answer]
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2023/08/21
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<issue_start>username_0: I recently submitted a paper to a CS conference which was accepted after about ~2 weeks. Upon acceptance they notified me that reviewer feedback was withheld until registration was completed (~$490).
This seems quite predatory and a large red flag. I am fairly new to academia so my confidence is not absolute. Advice is appreciated.<issue_comment>username_1: Looks like Springer publishes their proceedings -- <https://link.springer.com/conference/sai>
I recommend looking at the editors of previous proceedings, citations from the proceedings, ..., to try to gauge the reputation of the conference series.
Upvotes: 1 <issue_comment>username_2: We do not comment here on a specific conference. While withholding reviewer comments is unusual, in itself it is not a red flag or proof that the conference is predatory. If you submit a paper, you oblige yourself to attend the conference which means paying conference fees.
The short time to acceptance is however a "red flag" as is the wide-open call for papers. You can look at other conferences in the same line, look at some of the papers there and whether they are cited and you get a better idea whether this is a reasonable conference or not. You can also look at the sponsoring institution.
Upvotes: 3 [selected_answer]
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2023/08/21
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<issue_start>username_0: I am a PhD student studying theoretical physics at a US institution. I am now beginning my fourth year in the program, and struggling to solve my first research problem. I see PhD students around me keep writing papers while I am still struggling to write the first one.
My advisor suggested a research problem that I am now working on. He is not helping me with the technical details of the problem, haven't suggested papers to read etc., but he suggested that, since I have been struggling with such a simple problem for a long time, then this is a sign that research is not for me.
As far as I know, I am not stupid. I passed all the qualifying exams and got the highest grades in all grad physics classes. I am also fascinated by the subject, so I do not know why I cannot solve the problem. I spent a great deal of time reading and trying to understand the subject (which is quantum field theory). However, I can not solve problems.
My questions are:
1. how does one approach a research problem (say, in theoretical physics) and solve it in a reasonable amount of time while absorbing the prerequisite background knowledge along the way?
2. What distinguishes PhD students who are productive in their PhDs and how do top researchers approach a research problem and solve it? is it talent? breadth of knowledge? or time management skills?
3. Is my advisor correct that struggling with a basic project for a long time is a sign that I lack the research talent? I came to do a PhD in physics hoping that someday I will be a top researcher in my field, so I am trying to see how to improve and become more productive.<issue_comment>username_1: To move from a student to a successful researcher, requires insight. Insight into the nature of problems that is deep enough to suggest solutions that might be worth pursuing. Those solutions aren't obvious and the insight is built on a strong base that you develop as a student, but insight is of a different nature.
One way I developed insight (math analysis) was to solve, by hand, a very large number of similar problems. Eventually I could look at a formula and understand it without the computations. That was the start (only the start).
Insight gives you the power to think about things that "might" be true and the skill gives you the power to test them.
It took Einstein ten years of deep thought and discussion with a few other people to come up with Special Relativity. That development was one of insight building and constant return to the problem at hand.
You might talk to your advisor about this sort of thing. What is it that you are missing in your level of insight that is holding you back.
---
Note also that some problems are harder than they appear. Research is looking into the unknown and there are no guarantees about success or especially about timelines. Math, theoretical physics, and some parts of CS are like that. Probably the same in other fields as well.
If you talk to your advisor about what approaches you have taken to solving your problem, you can get feedback on whether those are naive or not. If they are, then you probably lack insight in some way. Otherwise, you are dealing with a problem that may be much harder than it seems. Hopefully you have an advisor sophisticated enough to help with this.
Upvotes: 5 <issue_comment>username_2: I'm a fellow Ph.D. in theoretical physics that used to struggle with research, and occasionally still does, after two post-docs and one teaching position.
To succeed, I think you need to give yourself time and significantly change your mindset. As others have mentioned in the comments, part of the process is to become able to solve problems independently. And I mean textbook problems first. The only way to do so is to solve them on your own without looking at other people's solutions. Every little detail counts, every small derivation, every little disappointment. Often you need to sleep on problems and approach them again with a fresh mind, and, quite often, you need to ditch your approach for a new one worse comes to worst. But you need to fail a lot of times first.
What helped me realize these things was a teaching appointment that led me back to research after it was over. It helped me see myself through my students. Undergrad education is concerned with solvable, well-behaved problems for which even a closed-form solution often exists. Research is completely different. You often resort to unorthodox methods, new approaches, etc. After all, it's supposed to be new knowledge. And it won't come in a linear fashion (most of the time).
Another problem I faced was my ego. I couldn't accept that I was unable to solve even simple problems sometimes. Accepting it helped. Heck, I even accepted I'm not as smart as I thought.
Regarding your advisor, I must respectfully disagree with him. If you went all the way to having a physics degree, you can go further. But there needs to be that "phase transition" I'm describing above.
Much like the ABCs, physics research has its ABCs. You need to know the fundamentals of Classical Mechanics, EM, Thermo, Stat Mech, Quantum Mechanics, etc. Then you need to learn Math Methods, numerical methods, coding, etc. It's a hell lot of things so that needs time and guidance. Sometimes, it might be better to stop, take a step back, and assess what went wrong and try again. Try, fail, try again, fail again, etc. Sure, some lucky ones are extremely intelligent and get it on the first try. Most people don't though.
One last thing. Just jump into a problem and enjoy the process. Enjoy what you learned. Develop consistency. Spend some time on it every day. Get a small result. Discuss it with your advisor or some collaborator. Keep moving. Find friends and collaborators. Go to conferences, and keep discussing with people. Socializing that way helps. You need to find some passion for it. Be bold!
Upvotes: 5 <issue_comment>username_3: To be successful in research, you need some combination of the following:
1. Background/breadth: You need to understand the problem(s) that are relevant to your field. Why are they worth solving? What makes them difficult to solve? What has been done before? The more problems you are familiar with, the more likely you are to find one that you can address.
2. Insight: Most problems are solved by applying existing ideas/techniques/tools/data/etc in new ways. Can you read papers from another field, understand the gist of what they do, and identify how that might translate to your area of interest?
3. Logical reasoning: Can you systematically evaluate a problem and potential solutions? Are your arguments watertight and convincing?
4. Technical skills: Maybe you're good at taking rats apart. Maybe you're fluent in Ancient Sumerian. Or COBOL. Anything that lets you do something that others couldn't.
5. Tenacity: Sometimes, if you keep bashing your head against the wall after everyone else has gone home, you'll find the wall moves.
6. Communication skills: No matter how amazing your work is, if you can't convince other people that you've done something useful, was there any point?
7. Resources: Whether that's dead rats, compute time, library books or pencils.
8. Luck.
Upvotes: 6 <issue_comment>username_4: I am really sorry about your situation. Based on what you have indicated, in my opinion, your supervisor might not be doing his(her) work very well, which is to support you and help you to succeed. Autonomy and independence in research come with time and training, and PhD supervisors play a key role for this to happen.
Would you mind elaborating a bit more on the relationship with your supervisor? If you are not really getting support to your growth from it, it may be better to quit and start somewhere else. I am curious that you had not got input from your supervisor even for simple things as suggesting a paper to read.
On the other hand, be cautious when it comes to comparing yourself to others, as every person undergoes a different learning process. Furthermore, not all research problems are the same in terms of difficulty and the work required to solve them.
Soft skills, such as time management, are also important to succeed. Time management is more than just filling up a calendar with things and there is a "science" behind that. You may benefit from training in this respect. You find valuable tips about this on the internet and there are some courses available on platforms like Linkedin Learning as well.
You may also want to read this article:
[Nature article on failed PhD](https://www.nature.com/articles/d41586-023-02603-8)
Best wishes,
AME
Upvotes: 3 <issue_comment>username_5: >
> Is my advisor correct that struggling with a basic project for a long time is a sign that I lack the research talent? I came to do a PhD in physics hoping that someday I will be a top researcher in my field, so I am trying to see how to improve and become more productive.
>
>
>
I think it is important not to see this as an evaluation of your personal worth. As you have pointed out, by becoming a PhD student you have proven that you possess the necessary skills and qualifications. Your lack of success can be due to a multitude of factors, some of them may be the fault of your supervisor (e.g., he might be misjudging the simplicity of the problem or not providing enough guidance) or due to bad luck (e.g., you have chosen a field or a problem that are not suitable to your abilities, or your best skills are not really for this type of the problem.)
It might be also that you are less suitable for *academic research* - which does not mean that you are a bad researcher. After all academic research is a pageant, where the winner is not always the most intelligent one - success in academic research is also about choosing fashionable problems, publishing your results quickly, popularizing your achievements, making connections, etc. There are plenty of examples of strong students who were given difficult problems, struggled and eventually abandoned academia, whereas more mediocre ones did good career, because they had a caring and/or influential supervisor or accidentally struck the problem that attracted much interests.
If the situation persists by the end of your PhD, you will have to consider changing career, rather than following a standard path PhD-postdoc-professor. On the other hand, if this is just your first year and your professor makes such remarks, it is more reasonable to consider changing the supervisor.
Upvotes: 2 <issue_comment>username_6: Given that it is Y4, then you must be mindful of the danger of PhD failure above all.
I feel that you need to refer to the Head of Department and get some *positive* input from beyond your superisor.
It's likely that you took on an easy-looking problem that had a share of hidden complexities. A [brontosaurus of complexity situation](https://www.engr.colostate.edu/ECE567/Lectures/01.28.15/SysML%20for%20Syst.%20Eng.%20Chapter%201.pdf), as they say.
I am surprised that this matter hasn't come to a head earlier than year 4 of the program.
Supervision is certainly in question here.
But so is your own lack of alacrity in either seeking another problem or getting more help with your approach to it.
So go see your HoD and seek informal views from other staff (if possible).
I've ignored your question of what distinguishes top researchers from mediocre ones. The answer I believe is humility and perseverance. Luck will help a small few researchers make a splash. But without the latter two virtues such fortunate success will be lost in either hubris or lack of will to make further advances. But right now you need to focus on being a competent researcher not a top one.
Upvotes: 2 <issue_comment>username_7: "He is not helping me with the technical details of the problem, haven't suggested papers to read."
Unable to evaluate *you* as a researcher, I can though safely say that your advisor has failed his job. Perhaps a prominent scientist, he is a plainly bad teacher.
My son wasted several years under the supervision of such an advisor, a man equally famous for his scientific accomplishments and his total disregard for his graduate students. While staying in his group, my son devised a clever strategy of creating collaborations with people, from both his university and other schools, who had experience in the area and were interested in the problems suggested to my son by his then advisor. In collaboration with such people, my son published several good works; and I would say that at that time those colleagues were effectively acting as his true advisors. Eventually, my son found a decent advisor at a different university, quickly wrote his thesis there, and got a postdoctoral fellowship at a stellar place. I would emphasise that the new advisor was not a world-known scholar -- but was a dedicated teacher caring for his grads.
In short, this is what I would do:
(a) Through publications or word of mouth, try to find people working on this class of problems. Get in touch with them. See if any of them could be interested in collaboration. (Don't be shy!)
(b) Meanwhile, look for a better advisor, at your school or, perhaps, elsewhere.
(c) Last, and by no means least, do NOT believe your advisor's words that "research is not for you". Do NOT let him discourage you. Quite possibly, you are not genius -- but one does not to be genius to write a PhD thesis. And in the situation you have described the principal problem is not you but your worthless advisor (who may at the same time be a brilliant scholar, why not?).
Upvotes: 3 <issue_comment>username_8: >
> My advisor suggested a research problem that I am now working on. He is not helping me with the technical details of the problem, haven't suggested papers to read etc., but he suggested that, since I have been struggling with such a simple problem for a long time, then this is a sign that research is not for me.
>
>
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This is absolutely an issue with your advisor not providing sufficient supervision, mentorship, and training. A friend of mine was told by an advisor that they'd never met anyone who got accepted into graduate school who wasn't capable of finishing grad school. Grad school is about training to become an independent researcher. Being good at that isn't some innate quality. It's a collection of skills that you learn, develop, and refine over the years through guided practice.
For a few years, I struggled to make much progress with my proposed dissertation project (analytical work in theoretical astrophysics). I was stubborn and kept telling my advisor and committee that I could do it, but eventually had a proper conversation with my advisor. I needed to finish my dissertation and the only way for that to happen was putting the original project on the shelf and shifting to projects I could complete in a more reasonable timeframe. I met with my committee members and other colleagues I'd met over the years to chat about other research projects. No one ever told me my lack of progress meant I wasn't cut out to do research. Your supervisor shouldn't be saying that to a student.
Does your programme require students to have a committee? If so, how often do you meet with your committee? Do you know their thoughts on this situation?
I'll emphasise again that I don't think you're the issue . I think it's an issue with your advisor. Are there other faculty or postdocs in your department or whom you've worked/interacted with that you could reach out to? A new (related) project and some extra guidance could make a world of difference.
To answer your questions:
1. Get help. Trying to complete a project in theoretical physics as a graduate student without having regular help, guidance, and feedback is extraordinarily challenging. Are you struggling with developing the requisite skills? Go through relevant sections/chapters in a grad-level textbook and foundational papers. Chat with other researchers in your group and department (students, postdocs, faculty, etc.) when you're stuck. Unsuccessfully trying to figure it out on your own for several days (or even worse, weeks) isn't an effective use of time.
2. Good supervision, mentorship, and guidance.
3. Nope.
Upvotes: 0 <issue_comment>username_9: >
> Is my advisor correct that struggling with a basic project for a long time is a sign that I lack the research talent?
>
>
>
No. What might be lacking is the skills of project management, people management and expectations management. Notice how I repeat three times the word *management*. Tons of persons in research world are not “popular” by the bizarr rating metrics of todays research community. Stay bold and clear the issues in your path without looking what others do.
Upvotes: 0 <issue_comment>username_10: >
> I am also fascinated by the subject, so I do not know why I cannot solve the problem.
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>
>
Not every problem is for everybody. Specialist fields such as your are as much art as they are science. Very few artists, in any field, are universalists. They like certain approaches and takes on the subject, and dislike or even disdain others. Perhaps that problem is just not your problem. And that's not to say that there is anything "wrong" with you. I'm an electrical engineer. I am supposed to solve a wide variety of problems, but there are only some that I really enjoy working on and got good results in. Even though my training was broader than that.
Look back at what you enjoyed doing in classes. There probably is some pattern there. Look at classes that were most specific to the sub-field you're facing in the research problem, and see if you can figure a way to build a bridge from what you know to what you don't know. Try to digest your knowledge gap into manageable chunks. Read what others wrote about the topic.
>
> I spent a great deal of time reading and trying to understand the subject (which is quantum field theory). However, I can not solve problems.
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I'd go on a limb and suggest: try explaining the field from basic principles to a non-specialist with some grounding in undergrad physics/engineering/mathematics. That's one way to evaluate your understanding. Explaining things so that a non-specialist could solve a very simple textbook problem requires exquisite understanding first.
Whatever you find, no one should be suggesting that you're "stupid" - don't think that way. You clearly are not - just asking the question here is a sign that you see what's going on and try to do something to improve the situation.
Upvotes: 0
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<issue_start>username_0: I'm going to email a potential supervisor for a PhD opportunity in aerospace engineering (astrodynamics curriculum) for introducing myself and getting more information about the PhD. I would like attaching my CV to the email, but I have some doubts about its formatting. After some online research, I'm realizing that I need to do some cleaning and remove some graphics from it. By looking at the attached photos, you can notice that the following graphical elements are present:
* sections icons,
* company/university/school/publications/academic projects logos,
* software/certificates logos.
**[EDIT]** Some clarifications:
* "The QR code on the top right" can be used to get an updated version of my CV without me having to send it every time (I removed the link before posting the question).
* "The QR code for saving contact info" can be used to save my contact
info on the smartphone by few taps.
* "Areas of interest": Should I replace with "research interests"? I want to use some keywords to show my favourite academic topics.
[](https://i.stack.imgur.com/YrbUk.png)
[](https://i.stack.imgur.com/h4JSB.png)
My questions are:
1. May I insert theses (B.Sc. but mainly M.Sc.) supervisors or references section (or both)?
2. What about graphical elements? May I maintain something or remove it at all?
3. Do you have other tips?
**[EDIT]** P.s. The opportunity is at a Spanish university, but I could also request information about a UK PhD call.<issue_comment>username_1: While this wanders into the realm of opinion, I can offer a few personal preferences.
I'd prefer something simple, not flashy. Graphics aren't the fundamental element of your field.
I'd take out anything that isn't backed up by external evidence; soft skills, for example. There is no verification, just a claim. Your second page is just a claim - easy to say, hard to verify.
Languages in which you are fluent might be important or not. More important for international students or if a particular language is essential in your field. Some places will require a test of language ability.
Some of the excluded stuff can go in a Statement of Purpose if required and if it backs up your career goals. Interests might go there, but probably not hobbies.
List degrees and awards
List publications and projects (probably separate lists)
List relevant work experience
Yes, saying who your supervisors were is fine, if not essential.
For the soft skills and other opinion-like things, let them come from letter writers, not yourself.
But, for me, simple. If it looks like an ad, I'll probably not be impressed.
Upvotes: 2 <issue_comment>username_2: Alright, as username_1 has said this will necessarily involve a significant degree of opinion.
**Background:** I'm a mathematician working at a German university and have worked for 1.5 years in an engineering job in a German automotive company (where I was involved in a number of job interviews).
The following might depend both on the culture of the field and on the culture of the country. But is it likely applicable in STEM fields throughout Germany and probably in a number of other countries in Europe.
**Summary.** I've seen this kind of CV format multiple times both in academia and in industry. Sorry for being so blunt, but I find the entire format utterly annoying.
**Drawbacks of the format.**
I hope you won't feel offended if I my language is somewhat pointed in the following comments. It is not my intention to be rude, but rather to give you an impression of the reaction that such a CV my lead to, at least for some people. (And again, this will likely be very culture-dependent; if you apply in a country which is culturally very different from Germany, it's probably best to completely ignore my answer.)
* The two-dimensional format (i.e., having information on the left and on the right) is quite messy. It's completely unclear (at least to me) which information goes to the left and which goes to the right. This makes it much more difficult to navigate the CV and quickly find things.
I'd strongly suggest to simply write things from the top to the bottom.
* The graphics and symbols. They don't make it easier to navigate the CV, in particular because their meaning is not 100% clear at first sight. So they add clutter without adding value. Everything that adds clutter but doesn't add value should be removed.
* Too many colours (again, the clutter vs. value thing). I you want to use colour for aesthetic reasons - why not. Then I'd suggest to use one color in addition to black. Nothing more.
* What's the purpose of the QR code on the top right? From looking at the CV I can't even say what is going to happen if I'll scan it.
* What's the purpose of the "QR code for saving contact info" on the left? You're applying for a PhD position. Who is going to use this QR code in which situation and to which purpose? Again, adds clutter instead of value - and causes the slightly annoying feeling that somebody strongly wants to use a "modern" gadget, without considering the value of that gadget for the specific situation.
* "Areas of interest" - what are you going to put there? I mean, you just got your degree. Any specialization you might have will probably clearly show in your transcript of record. If you want to somehow stress or explain your interest, it might be better to do it in plain text - maybe in the cover letter (or whatever text you are required or allowed to submit).
* A list of buzzwords to describe your "Softskills and strengths"? Don't. Just don't.
* "About me". This is my personal favourite. I've seen such a brief paragraph where people try to put a "catch phrase" or something similar in a number of CVs. Not a single time has such a paragraph contained anything that I found useful. If it has ever drawn my attention, then only to the fact that the applicant doesn't understand yet that this is a bad idea.
* "Aerospace engineer" in line three of the header. You're applying for a PhD position in aerospace engineering. Whoever reads this application will assume that you have a related background and will look up the details in the education section. Having the word "aerospace engineer" in the title doesn't add value (but, you guess it, clutter).
* "Hobbies and interests". Well, I don't know. It might be a nice list to put there if it contains something extraordinary (might still not be important, but might for instance make a good start for a bit of small talk at the beginning of an interview or something). I'd recommend against putting things such as "reading" or "watching movies" there. Everybody reads and watches movies (except for those who don't).
* "Certificates": Do the Matlab certificates mentioned there refer to those online courses that MathWorks offers about every topic one could think of? Well, I've seen some experienced Matlab users cringe a bit about mentioning those in a CV, but it might depend a bit on the person who reads the CV. Anway, probably not a big deal in any direction.
* In contrast to username_1 and to <NAME>'s comment, I find some of the information on page two quite useful. It's nice to know which programming languages you know (but I'd recommend to only put LaTeX there if you indeed have some serious experience with programming in LaTeX rather than just using it as a mark-up language; in the latter case it might be more appropriate to list it in the section "IT skills"). In fact, I'm currently mainly (though not exclusively) working on more theoretical topics in math, but if someone is interested in doing a PhD with me, I still find this information useful for various reasons.
One issue is, of course, that the "skill level" as it is written in the CV is completely subjective. But it still contains some information, in particular as I can compare the levels that you put there for different languages and as I could discuss the matter with you in an interview (in case that I'd find it sufficiently relevant to discuss it).
* Similarly for the "IT skills". Well, I personally wouldn't be interested in some of the software that you mentioned there, but this probably really depends on the field - and I can't tell about aerospace engineering, so I can't give particularly useful advice here.
In any case, if you mention your level of skill on two different sections ("IT skills" and "Programming languages"), I'd strongly suggest to use the same layout to depict them.
**What to do?**
In addition to the single points mentioned above, I have one general suggestion: throw away the template and use a different one with a simpler and clearer layout. In case that you use LaTeX for the CV: in math I've seen many people use the class "moderncv" which is well-aligned with keeping the format simple. There are certainly further nice classes, too.
Upvotes: 3 <issue_comment>username_3: You mentioned
>
> ... *email a **potential** supervisor for a PhD* ...
>
>
>
You can make do with a one pager
* the QR code link on the left can make way for 'Programming Skill'
* the *Programming Skills* will fused your current \*programming languages and pointers of your IT skills (vss, numerical simulation, data analysis, office automation)
* you can do away with soft skills and strengths
* likewise, you can discard *Certificates* (inbtw, MATLAB is already showing prominently in your 'CV')
* feel free to yank off *High School Diploma*. This can come in at the formal application stage.
* Academic/Research Project: rather than listing out, I'll perhaps write each up in paragraphs showing my research competency and relevant accomplishments/outputs.
In my view, what you have currently, comes out as a CV for an entry-level position. It doesn't show much of your ***research capabilities and potential***. Note that, opinions will vary from country to country.
I'm not a two-column CV person but that does not negate that others prefer or even adore them. Whichever way, ***showcase your research*** capabilities/abilities.
---
You can have two CV, one for this initial contact with potential supervisors (one pager) and second (2-pager) for the actual application along with statement of purpose
Upvotes: 1
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<issue_start>username_0: A curiosity inspired by [this answer](https://academia.stackexchange.com/a/200411/120628) by user [Allure](https://academia.stackexchange.com/users/84834/allure), on a previous question I had regarding how to recognize predatory or otherwise disreputable journals.
In the answer, it is noted that journals publishing subscription content are generally trustworthy, which seems quite reasonable, since nobody wants to pay to read (presumably) rubbish papers. Indeed, in my experience predatory publishers also tend to be Open Access, although of course the converse isn't true. My question, however, is about exceptions to this rule: are there known predatory journals (defined as being on any standard black list, such as [Beall's](https://beallslist.net/)) who also offer subscription content?
Note: there are journals whose reputation [has significantly changed](https://academia.stackexchange.com/questions/124807/has-a-journal-ever-switched-between-being-a-predatory-journal-and-a-reputable-on) (and of course many journals have revised their subscription rules). My question, however, is about journals that *at the same time* are (or have been) both predatory and pay-to-read: are there any such cases?<issue_comment>username_1: Academia.SE isn't about providing lists and evaluating specific journals is off-topic here. However, I can write a more vague/general answer.
Open access is a newer model than predatory publishing, even if the term was created with open access journals in mind. Though standards vary by field, "page charges" as well as fees for things like number of figures (often more expensive for color) were common in my field (including in reputable journals), while those journals still collected subscription fees and were *not* open access. Therefore, predatory journals still existed to collect those fees. Open access has merely made the publishing step more expensive for those legitimate journals, and made a predatory mimic of that model more lucrative.
[Vanity press](https://en.wikipedia.org/wiki/Vanity_press) has also been around for a long time as a term that shares a lot with the predatory journal publishing, but may use different mechanisms for extracting funds, such as offering to pay authors royalties while also requiring authors to secure a certain number of books up-front (example: "we'll pay you $30 per $100 book published, but you need to sell at least 100 copies! You know, Every Author You Ever Heard Of does this thing where they actually start things off by buying 100 copies right away and sharing them with friends to get people interested! So yeah, that'll be $10,000 please!"). The scam is that the publisher doesn't actually expect or intend anyone to be interested in the book except the author themselves. Or, they may push payment for for editing costs ("your book is almost good enough to print, but we'll have our editors get it up to industry standards for $2,000"). The publisher doesn't actually spend that money on editing.
There's no "open access" in these models, but they're still extracting funds from the authors up front. Some of them may even legitimately sell copies and even pay royalties, just like some journal publishers with predatory tactics still do some level of peer review (for at least some submissions).
Upvotes: 3 <issue_comment>username_2: This question is more complicated than one might think at first sight. Under the traditional definition of "predatory publishing" - where one does not conduct peer review and publish everything - then the answer is clear, there are no predatory journals which are subscription-based. You hit on the reason why not. The primary buyer of subscription content is libraries. These days one of the key tools libraries use to determine what to subscribe to is usage statistics. You need people who use that library to land on your journal's webpage and attempt to access subscription content, a lot, and then you might be able to get them to subscribe. If you publish junk, you won't get these so-called 'denials', and you also get no subscribers. Predatory publishing simply did not exist before open access, for a reason.
However the definition of "predatory publishing" has become nebulous, and these days you get people defining all sorts of things as predatory:
* If the publisher sends you [unsolicited marketing emails](https://academia.meta.stackexchange.com/a/4716/84834) (you probably can't see this till you have more rep however)
* If the publisher charges you to read the articles or the authors to publish the articles (thereby making all OA journals predatory)
* If the publisher [publishes journals without disclosing the funding source](https://www.the-scientist.com/the-nutshell/elsevier-published-6-fake-journals-44160)
* If the publisher sends reviewer invitations which are beyond the reviewer's expertise ([every editor does this to some extent](https://academia.stackexchange.com/questions/193135/how-often-do-editors-reach-reviewers-whose-expertise-dont-match-the-paper))
* If the journal has a large editorial board but very few articles are published per year (which to insiders indicates the journal is unhealthy, but not that it is fraudulent)
* The journal purposefully publishes controversial articles in the interest of boosting citation count (which makes [*Nature*](https://en.wikipedia.org/wiki/Water_memory#Publication_in_Nature) and [*Science*](https://en.wikipedia.org/wiki/GFAJ-1) predatory)
* The author must pay APC or publication fees before submitting the article ([which makes many journals in economics, finance and accounting predatory](https://www.elsevier.com/authors/policies-and-guidelines/submission-fees))
Suffice to say, virtually every publisher in the world is predatory, depending on your definition. Put another way, you can find people who think virtually every publisher in the world is predatory. Therefore, there is no meaningful answer to your question unless you first define what predatory is. [Good luck](https://academia.stackexchange.com/questions/124807/has-a-journal-ever-switched-between-being-a-predatory-journal-and-a-reputable-on/124824#124824).
Upvotes: 2 <issue_comment>username_3: I know of at least one physics “journal” with the following properties:
* A hybrid financing model: You need to pay to publish **and** to view. For whatever it’s worth, the prices are considerably below the respective ones for real journals that are only pay-to-publish and pay-to-view.
* The journal caters primarily to cranks, but you also occasionally have what appears to be clueless scientists from developing countries publishing regular (but possibly irrelevant) research.
* The journal claims to perform peer review. Articles are accepted within months (which is normal within the field).
* As you need to pay to view, I have only ever seen one paper e-mailed to me by its author (unsolicited). However, I have looked at quite a handful of abstracts. The vast majority of these are far below normal publication standards. Any peer review is clearly not effective.
* A considerable fraction of the editors the journal lists are dead, some since over a decade. Most editors were unresponsive. One alive editor did not know about this honour and got his name deleted from the journal’s webpage after I mailed him. ([More on this](https://academia.stackexchange.com/a/154008/7734).)
* The journal appears to be published privately by one or two people.
* I cannot find the journal on any list of predatory publishers (other than lists of journals de-listed by Scopus), but it’s worth noting that many on these lists exclusively focus on open-access publishers.
*Naming the journal here would be against the ethos of the site. However, if you know your synonyms, it should be easy to find this journal and judge for yourself.*
Obviously I do not know the finances of the journal and I cannot divine the real motivations of the journal’s publishers: They could be predators milking cranks or they could really believe in their cause and be just covering their expenses. So whether this meets your definition of predatory journal is up to you.
Either way, I would argue that what’s more important is what it means to publish there (or be listed as an editor):
* You spend money for publishing.
* There is effectively no peer review.
* A publication or editorship will be as worthless and damaging as one in a typical predatory journal.
This is the same as for a classical predatory journal and thus you can [treat it like one](https://en.wikipedia.org/wiki/Duck_test) when advising authors potential authors (and editors).
Upvotes: 3 [selected_answer]
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<issue_start>username_0: A few years ago, I graduated with both a master's and bachelor's degree from a globally ranked top-10 university. My overall classification was an average upper-second class (UK) - which is around a 3.4-3.5 GPA for the US-based. For context, an upper-second lies in the range of 60-69 whereas a lower-second lies in the range 50-59.
I applied broadly to PhD programs a few years ago but was rejected by all. My master's thesis advisor and postdoc that I worked with both agreed to write me letters of recommendation but perhaps they were not strong enough - hence, my rejection.
I have spent the past few years as a software engineer in industry detached from academic research, yet after much reflection, I am sure that I would prefer a career of research over my existing trajectory as an SWE.
Despite this, I do not have the "raw material" to put together a competitive PhD application (as outlined by the evidence above), and so am wondering how to get into a good PhD program.
I am considering doing a second master's thesis with the aim of doing more research with new professors, and then using that as a springboard into a PhD program. The aim is to get better recommendations, a better SoP, and maybe a publication. Is this a sensible idea? Will it ultimately make little difference to admissions committees? Or is there a better way to strengthen my application?<issue_comment>username_1: I think that you are approaching this exactly right. Most rejected applicants seem to be asking "how can I get over my low credentials without doing any work?", as if there was some secret button one could press and make past mistakes go away. You are recognizing where you did wrong during your masters, and have a plan to do better next time. You seem to be correctly guessing that you didn't get great letters, and that's OK, as not every student can be above average (actually, about half are below average, ha ha). But since you will be correcting the issues, you will probably get better letters next time.
Graduate school admissions are not a test of your worth as a person nor an evaluation of the totality of your life's choices. It's just an attempt from the admissions committee (or department, or PI) to answer the simple question: is this student, as they stand now, ready to produce some research? If the answer is yes, you get admitted.
So yes, as long as you do things differently this time, doing another Master's will increase your chances of admission.
Remember that you don't have to be admitted by all the programs you apply to, but only one.
Upvotes: 2 <issue_comment>username_2: >
> ... I am considering doing a second master's thesis with the aim of doing more research ...
>
> The aim is to get better recommendations, a better SoP, and maybe a publication.
>
> Is this a sensible idea?
>
> Will it ultimately make little difference to admissions committees?
>
>
>
I understand you're speaking in the UK context. In that regard, your action plan (of a second MSc) based on your aim should take you closer to your desired outcome.
In that regard, I'll recommend you give MRes and MPil a shot. If you manage to get into them, you might transition better into PhD.
All the best.
Upvotes: 0
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2023/08/22
| 388
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<issue_start>username_0: To conduct my study, I had to use thousands of lines of **R code** to generate random data and to do analysis. Now, when I am going to submit my manuscript to my targeted journal, do they ask to provide all the code? As I never submitted any article before, so I don't know what to do!
I have read the instructions from the journal. From there I got to know about **figshare**. Should I upload all my R code there first and then after getting *DOI*, try to submit the manuscript by adding the DOI in the **data availability statement**?<issue_comment>username_1: First, this depends on the journal and its data availability policy. The prime arbiter is the editor or associate editor of the journal. You can contact them on what they would find most convenient for their process.
Second, a paper and therefore possibly the data you generated is likely to change during the review process. If you think that your R-code is unlikely to change, you can go ahead and put it in a public repository. Otherwise, you can offer to put the code in a zip file and make it available to the reviewers with your submission as supplementary material. Depending on your paper, reviewers might just believe that you were working appropriately and not used e.g. a flawed random number generator. There are other ways to make the material available to the anonymous reviewers.
Getting a DOI now seems to me to be premature since the contents of your supplementary material might still change.
Upvotes: 3 <issue_comment>username_2: I would use GitHub or GitLab to track my code and then issue a DOI once the paper is accepted and the code will no longer be edited (either to a GitHub tag or a figshare page).
Upvotes: 2
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2023/08/22
| 1,196
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<issue_start>username_0: I'm leaving university soon and the academic email address I've been providing in my research papers and academic contacts to reach me will be deactivated by the end of November.
What action should I undertake not to lose them?<issue_comment>username_1: Your university may be willing to extend the life of your address upon request. They might also be willing to forward any mail to that address to another that you specify. I suggest that you ask and if they agree, provide them with an address that you control, perhaps gmail (not an endorsement).
Otherwise it is pretty difficult. Over time you can do things to make yourself visible (personal web page, for example) and update your address individually with your contacts.
Ask co-authors to forward mails to your permanent address when inquiries about your joint papers are made. Update editors on any email changes so that enquiries to a journal might (just possibly) come to you.
If you are "corresponding author" on a paper, use an email address that will endure.
But I also encourage universities to help students, especially graduate students, to remain visible through old email addresses. My own (former) university has done this to (at least) some extent. If yours doesn't, then perhaps you can convince the faculty there to demand it.
At one time Dartmouth College promised to make all student email addresses endure forever. I thought at the time that this was a brilliant move for purposes of maintaining contact with alums if nothing else. I don't know if that policy is still in place.
Upvotes: 3 <issue_comment>username_2: Based on username_1's answer and the comments, I still think you should try to make forwarding a policy.
Assuming that isn't going work; *right now* download all of your email and extract the addresses of those with whom you've corresponded. At least, you'll be able to contact them in the future.
Add a .sig to your email saying, "I'll be leaving this address soon. My personal website, <https://example.com>, has contact information."
If you don't have a "permanent" email address, get one. Gmail is free, and paid addresses are not expensive. Begin referring people to that address *right now*.
Upvotes: 4 <issue_comment>username_3: What you are experiencing is a common issue, and I don't know why there's no standard solution. Every time you move up the academic ladder, a new email address and lots of people who need to find a way to contact you.
I know this does not help you now, but the preventive measure is to use a personal email address for all correspondence, e.g. a Gmail account. Every year this seems to be more common.
Since you already have your institution's email listed, the best thing to do is to make sure that your personal website is easy to find through Google, and that your new email address is listed there. I know, that's not easy for <NAME>, <NAME>, and <NAME>, but might be a solution if your name is uncommon. Even if your name is common, make sure that the text of the website includes lots of keywords related to your research, to help those looking for you. If your new institution provides space for personal/research webpages, make sure to use it, as these are ranked high by Google, as opposed to some @wordpress site. Also make sure to keep an active profile in academic social media sites like Researchgate, and even on sites like LinkedIn. That way, people can find you quickly.
I hate anything smelling of social media, and don't want to be served ads while reading email. When you use commercial "free" services, you are at the mercy of the company changing their terms. So my own solution has been to pay for my own domain and email address. The cost is <$40/year and gives me a permanent email address that I control. I find it's worth it.
Last, it used to be the thing that people would send email messages with "I've changed my email, please update your address book." These were sent to their whole email address book. I can't speak about the effectiveness of this approach, but since social media took over, I've been receiving less of that type of message.
Upvotes: 4 <issue_comment>username_4: Prevent this situation
----------------------
This will not help you today, but it might help another person in the future:
1. Get your own domain name and hosting service.
2. Create an email address for your domain.
3. Create a web page for your domain that lists your contact information.
4. Always use your own email address to send emails instead of the one your employer provides.
5. Forward your institutional emails to your personal address. They may refuse to forward after you leave, but in my experience they will forward emails while you work there.
This looks more professional/official than a Gmail account.
I have used this method for many years with several institutions. I have never needed to update any accounts with third party websites or tell anyone my email address has changed. I have never lost emails because the institution removed my account.
Refusing to use my institutional email address has never caused me any real problems. I do occasionally get confused questions about it, including questions from people who do not understand where domain names come from.
Upvotes: 2
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2023/08/22
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<issue_start>username_0: I am looking to apply for a PhD position at a UK university but I desperately feel I am in a catch 22 situation. What I've read online, is that supervisors are very busy and receive many such emails so before contacting a PhD supervisor, I need to get familiar with their research.
I contacted several supervisors, becoming familiar with their research beforehand. One had no PhD students and said he does not take PhD students. Another had 2 and said he's not looking to take more. Another supervisor with 5 students said he's at maximum capacity. The picture continues.
It takes me awhile to become familiar with a supervisor's research. In addition, it is not like I don't have anything else to do and I feel I am shooting in the dark here.
I am an experienced professional, I've got a good level of academic knowledge and commercial experience, an undergrad from the top university in the country and I am looking to self finance a PhD - in effect to pay to work. I don't understand why it's so hard.
Do you have any advice for experienced professionals applying for a PhD?<issue_comment>username_1: I know that academia sometimes resembles a closed union shop: you need to be a union member to get a job, but you can only get membership in the union through having a job in the first place.
What you describe is normal. It is common for professors to have a full lab, not be taking students at the moment, etc. It is also common for famous professors to receive many emails from strangers saying things like "My dream is to get a PhD from Prestigious U., would you take me as a grad student?", and answer those emails with "not taking students now."
What you need is a way to narrow down your list of prospective professors to only those that might be taking students, and then to try get an introduction. A few ideas:
1. Speak with your professors at your undergrad institution, tell them about your academic interests and ask if they know anybody looking for a good graduate student in the subject. If they don't know, ask if they can recommend someone who does.
2. When you first contact a professor, just say that you have interest in their subject, and if they can recommend any other person in the field who might be looking for graduate students.
3. Attend a few conferences in the field, and approach people with interesting posters, and introduce yourself as a prospective graduate student. Again, ask if they know anybody who has graduate student openings.
Once you have a reference, write to that person saying that so-and-so said they might have an opening for a graduate student, and that you'd like to learn more about the research they are doing.
Remember that just like in any negotiation, this is a dance. You send feelers out there to see who's hiring students, and professors send feelers through their network asking for students who might be looking for a PhD position. Once the two meet, the professor tells you a bit about the deal, you tell them about your interests and goals. If you both like what you hear, you go on to the next level and visit the lab/research group, etc. And so on.
Upvotes: 4 <issue_comment>username_2: Further to @username_1's sound advice: In the UK, academics who *do* have places available for PhD students often publicly advertise the fact. One common location for such advertisements is , more specifically <https://www.jobs.ac.uk/search/phds>.
Upvotes: 4 <issue_comment>username_3: In the UK, a very large portion of PhDs (particularly externally funded ones) are on a reasonably strict schedule, and must be externally advertised and filled through a (semi-)formal recruitment process. So it's relatively uncommon for a supervisor to have a funded PhD in their back pocket that they could offer to a cold-calling candidate.
Instead, it's worth looking at advertisements - on university websites, [Jobs.ac.uk](https://www.jobs.ac.uk/) and particularly [FindAPhD.com](https://www.findaphd.com/) for positions which are coming up. This will at least guarantee that the potential supervisors both have an interest in supervising, and the resources to do so. You should also bear in mind timelines - most PhDs are aimed to roughly align to the academic year, so starting September-October, and will have already recruited for the upcoming round.
(This advice may be less relevant in some fields where funding and projects are more student-led, as in some areas in the humanities.)
Upvotes: 4 <issue_comment>username_4: *I am an experienced professional, I've got a good level of academic knowledge and commercial experience, an undergrad from the top university in the country and I am looking to self finance a PhD - in effect to pay to work. I don't understand why it's so hard.*
Me neither! And I led a large STEM research school at a top UK university.
*Assuming* the above in italics is all true, it really should not be hard to find a position, and you should feel no hesitation in contacting academics who evaluated your work in your final year at uni - they may be able to advise on who might be a good fit for you, and willing to take you on.
Upvotes: 3 <issue_comment>username_5: Here’s how I did it—though I was (and am) in the US and was already enrolled at the university. I just started taking a fairly broad range of courses that would help me eventually pass the qualifying exams anyway and, more importantly here, struck me as really interesting and exciting to study. In this way I also got to know the faculty members who taught them, and they got to know me.
Unless you must have a relationship with a supervisor locked down before you leave the starting gate, I warmly recommend this approach. The faculty member who eventually became my advisor had by then concluded for himself what my abilities were. And another benefit was that when it eventually came time to enlist the members for my dissertation committee, I had more than enough great choices of individuals who knew me, my work, and the fields to which it was relevant.
Upvotes: 0 <issue_comment>username_6: As someone that walked away from my PhD despite getting funding from EPSRC and doing the full 3 years, I would like to highlight some alarm bells here. I chose not to submit my thesis.
I have to *explain away* all the different reasons of why I don't actually have the final PhD when I apply for contracts/jobs but that's actually gone down ok. There is a big threshold in Data Science for candidates to have a PhD and I'm literally having to work in the opposite direction to explain why I, effectively, failed mine. I'm doing ok from this.
My concern here is that you're scatter-gunning to try get a PhD for the sake of it. "Oh, you study flimflams? I can probably get behind that; can I be a student of yours?". There's nothing in your question that suggests you have some burning desire to study a *specific* thing, and that probably comes across to the academics for someone of your age, and I question the utility of the qualification unless you're looking for a career shift into academia.
Upvotes: 2 <issue_comment>username_7: The alarm bells for me at least would be your self funding. You need to expand on this in your contact emails.
How exactly is this going to work, will you have a full time job alongside a full time PhD? This will not be attractive to a supervisor and verges on impossible.
Or does this money already exist? Just the other day I had a request for supervision from a student with funding from the Saudi government, we get a lot of these of varying quality (and I'm not yet a group leader so this one really had not done their research) so you'll need to stand out from them.
Is the money just to cover your fees, or are there other costs involved in the research you're not even aware of? Lab PhDs for example will need bench fees, consumables, and potentially other overheads that the university charges for support staff etc.
Upvotes: 1
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<issue_start>username_0: I want a tenure-track job in math. Is there anything else to know other than to publish a lot and have good teaching?<issue_comment>username_1: Publishing quality papers and excellent teaching help, of course. Quantity isn't the same as quality, however, and your teaching needs to be attested to in some way, perhaps through letters of recommendation.
Nothing is guaranteed, however. There is a lot of competition. There is a personality aspect: how you come across in interviews. Lots of things.
Times are hard at the moment. I was once a good prospect for a solid position but the economy cut the prospects to zero and it took me quite a while (and a change of fields) to get a tenure track job.
Good luck.
Upvotes: 3 <issue_comment>username_2: For tenure track positions with significant research responsibilities in pure mathematics in the US, evaluation is mostly by your best two or three papers, supported by a number of other papers. Realistically, to even be considered these days, you need two or three papers that are in either a decent general journal (e.g. at least Israel Journal, but preferably at least Advances in Math) or a top subject-specific journal (e.g. Algebra and Number Theory). Beyond that, you also need roughly a paper per year after your PhD.
Expect this to be a moving target as the supply of jobs continues to decrease.
Upvotes: 1 <issue_comment>username_3: Academic job market is extremely competitive at the moment, and many tenure track jobs attract 100s applications per position, so the success rate is 1% or less. Hence, knowing nothing about you personally, I would say that, statistically speaking, no, you won't get a job.
The rest depends on you. How much effort are you willing to put and how many sacrifices are you going to make. How much debt are you willing to take on by doing degrees at prestigious places and studying for your PhD? How much are you going to delay getting your first paycheck, settling down or starting a family? How many weekends and nights are you willing to spend writing papers and not having a proper rest or seeing your friends and family?
tl;dr: You can get a tenure-track job in maths by publishing a lot. However, this lot could be a lot bigger than you expect.
Upvotes: 1
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2023/08/23
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<issue_start>username_0: I am looking for a PhD/job position. I sent an email to a group doing things potentially aligned with my interests. I had an interview with them and I am not enthusiastic about the project. I could see myself joining the group but the topic is quite far from my perfect topic.
They encouraged me to apply early to the doctoral school (they did not say they'd take me if I was admitted, but I think I do have some chances).
Fast forward one month and I haven't applied to the doctoral school, the deadline is still very far away, and I still want to find better options. They just asked me if I had heard back already from the doctoral school.
What could I tell them? My intention is not closing doors, but not stepping into this one too much either.
I could tell them that I still haven't managed to gather my references, which is true (I am in Europe, you don't always need reference letters for getting into a PhD programme), but not completely "honest", since there is a chance I will never apply to the school to take a job offer. Is it a good idea to just say I am still looking around and I will take time until the deadline, in case? They might start preferring other candidates if I ever was a top choice.
*Disclaimer*: this question is similar to [this one](https://academia.stackexchange.com/questions/13349/what-to-say-to-one-phd-offer-when-still-waiting-to-hear-the-result-of-a-differen), but substantially differs in the nature of the involved "offers".<issue_comment>username_1: Publishing quality papers and excellent teaching help, of course. Quantity isn't the same as quality, however, and your teaching needs to be attested to in some way, perhaps through letters of recommendation.
Nothing is guaranteed, however. There is a lot of competition. There is a personality aspect: how you come across in interviews. Lots of things.
Times are hard at the moment. I was once a good prospect for a solid position but the economy cut the prospects to zero and it took me quite a while (and a change of fields) to get a tenure track job.
Good luck.
Upvotes: 3 <issue_comment>username_2: For tenure track positions with significant research responsibilities in pure mathematics in the US, evaluation is mostly by your best two or three papers, supported by a number of other papers. Realistically, to even be considered these days, you need two or three papers that are in either a decent general journal (e.g. at least Israel Journal, but preferably at least Advances in Math) or a top subject-specific journal (e.g. Algebra and Number Theory). Beyond that, you also need roughly a paper per year after your PhD.
Expect this to be a moving target as the supply of jobs continues to decrease.
Upvotes: 1 <issue_comment>username_3: Academic job market is extremely competitive at the moment, and many tenure track jobs attract 100s applications per position, so the success rate is 1% or less. Hence, knowing nothing about you personally, I would say that, statistically speaking, no, you won't get a job.
The rest depends on you. How much effort are you willing to put and how many sacrifices are you going to make. How much debt are you willing to take on by doing degrees at prestigious places and studying for your PhD? How much are you going to delay getting your first paycheck, settling down or starting a family? How many weekends and nights are you willing to spend writing papers and not having a proper rest or seeing your friends and family?
tl;dr: You can get a tenure-track job in maths by publishing a lot. However, this lot could be a lot bigger than you expect.
Upvotes: 1
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2023/08/23
| 1,061
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<issue_start>username_0: I am an instructor for a local CS class (online). We are trying something new. We are offering a 17 week program for CS (programing). The program is divided into 3 sections of 5 weeks each and then 2 weeks for the final project. Every 5 weeks, new students are enrolled. This means now I have students who are in week 6 and week 1 (newly enrolled students). Class happens Monday - Thursday 6:30 PM - 7:30 PM. Students are required to read online resources, watch videos before coming to the class.
How do I manage such a class where every 5 weeks different students are getting enrolled?
My idea is to treat it like Office Hours. So students (no matter which week you belong to) can ask me questions and I can help them.
Any other suggestions?<issue_comment>username_1: What a horrible idea! You have students at three different levels in your class:
You can give it a lab like structure. Students work on their tasks and you can go from student to student, supervising, correcting, and mentoring.
You can give two groups a few tasks and then give a short lecture to the third group. After the lecture, you explain the solutions of the task. You repeat with another group being the focus group. This is close to a flipped class-room and you can pick up techniques from this setting.
If you make it like an office hour, you are going to miss out on the shy or lost students.
Upvotes: 2 <issue_comment>username_2: I hope that the administration views this as an experiment in which proven pedagogy isn't ready for prime time. If not, you will have some difficulty. If they do, then stay flexible and modify things as you learn more.
For an online class you can do the following with a bit of help from your IT department.
Establish a private mailing list. I suggest under the control of the university, not something like Facebook (privacy, security, ...). Subscribe every student to the list when they register. Unsubscribe them a bit after the course ends for them, say, when their grade is posted.
In addition to whatever you do online with zoom or whatever, have the students ask questions on the list. Everyone sees every question. Everyone sees every answer. If you can get the entire set of list interactions preserved and visible to all students, all the better.
I've used this in other situations with groups of widely varying background/experience. It is helpful even in more normal classroom situations because those when a question is asked it is often likely that others had the question and didn't ask it. The classes I taught with this tool met infrequently (once a month), but were 24 by 7 from the student standpoint. When they had a question, they asked it and got an answer, maybe from me, or not. But their progress was never blocked.
The list is used for everything except communication that is personal (grades ...). All content questions go to the list so everyone sees every interaction.
Encourage students to answer questions posed on the list - answers back to the list. This cuts your load immensely. You only need to respond to answers that might lead to misconceptions. But make sure that the list isn't used to pass answers to exercises to other students. Minimal hints are fine, but not answers. Perhaps questions about exercises can only be answered by yourself (or a TA).
Second, as much as possible, "flip" the classroom so that the real time sessions are not content delivery. Use readings for most of the content. Look for a way to encourage the readings on a topic prior to discussion in real time. A quiz on the readings is useful for this if you have the tools for it. The quizzes count somewhat toward the grade. Taking the quiz is the ticket to participate in the real time session if you can make that work. Graded quizzes might be enough. You might need three sets of quizzes, one for each "level".
---
Alternative to the open mailing list, if questions come to you and you post the important questions and your answers to a list so that all can see them. Then you don't get the same question ten times. But having other students answer questions is a big time saver, though you have to read the list frequently.
---
I could add more for a face to face situation.
---
Caveat. I can't predict how the students will benefit or not from seeing material "out of order" and with things at different levels "all at once". It might work fine, or it might be a disaster. You need to monitor that and give feedback to administration on your observations.
Upvotes: 3 [selected_answer]
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2023/08/24
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<issue_start>username_0: I find myself in a complex situation involving citations between a published paper and the thesis from which it originated. Here are the key details:
I submitted my thesis for examination and, during the 8-month review period, published a paper based on one of its chapters.
The paper was also accepted and published.
After submitting my thesis, I joined a new institution, which is the affiliation listed in the published paper.
Given this backdrop, I have two primary questions:
I passed the thesis examination recently and I am now in the final phase of revising the thesis. The paper was published two months ago. Should I revise the paper (by sending a request to the editor) to cite my thesis, or should the thesis cite the paper?
How should I handle the affiliation discrepancy? If the thesis cites the paper, it may appear as if the majority of the research was conducted at the new institution rather than the original university.
I'm concerned about how to ethically and accurately represent the relationship between the paper and the thesis, particularly considering the change in affiliation.<issue_comment>username_1: I have often found such a situation in PhD theses, as the papers were published during the PhD time and predate the PhD.
There is in such cases a section in the first part of the text, near the table of contents, list of figures, or acknowledgments.
>
> Some results from this PhD thesis have been published in journal articles
> ...
> List of references, with a full citation.
>
>
>
I have not seen, however, the reverse citation that you propose in which one would cite their own PhD thesis in a scientific article with the published results.
My suggestion is thus:
1. Leave the published paper as is
2. Cite it explicitly in your PhD thesis as resulting from the thesis work. You can even be more specific (i.e. "during the revision period of the PhD thesis, some results of chapter 32 have been published as Ref. [8147]")
Regarding the affiliation, one practice would have been to list your PhD affiliation with the current one. In many papers I have seen it as a footnote though ("1. This work has been carried out while author XYZ was completing his PhD thesis at Institution ABC"). If you are worried about this, I would discuss it with your PhD advisor though.
Upvotes: 6 [selected_answer]<issue_comment>username_2: I think you are too scrupulous.
At least in Comp Science and I assume in many other fields as wide apart as Theology, the first publications at your first institution after graduation will be usually based on the thesis. Similarly, if you were to change institutions, then your first publications at the new institution will be most likely based on ideas you developed at your previous institutions. Thus, your official affiliation is not assumed to be identical to the place where you did most of the work.
Changing citations after publications is very, very tedious. Do you want to have print versions recalled and replaced? Do you want the online and the print version be different? So, besides other reasons, there is no way that this is going to be a good idea.
There is no real need to cite your paper in the thesis, but if it makes you feel better, just say something in the introduction about parts of the thesis already being published. Different academic traditions feel differently about publishing the thesis before submitting it, so your location will determine whether this is a good idea. In the US, however, Ph.D. committees might want to see prior publications or even require it.
My main point is that affiliation is not equated with the place where most of the work was done. This idea might come from the tradition to thank the host institution in publications after a sabbatical leave for publications that were worked on during that leave.
Upvotes: 2 <issue_comment>username_3: If you publish the same contents in different places / different forms, it is good to clarify how they relate to each other and which one was first. In your thesis, you should clarify that work done for the thesis has meanwhile appeared elsewhere (as people have advised above). But it is also ok to advertise your thesis in the paper, perhaps as the longer version or the larger context in which it is embeddd.
Upvotes: 2 <issue_comment>username_4: I think that total transparency is best for everyone here--it makes it clear to readers what content overlap there is between the theses and the papers. Th introduction to my thesis had a section that basically looked like:
* Chapter 2: Show X result. Originally published in (citation)
* Chapter 3: Show Y result. Originally published in (citation) and (citation)
* Chapter 4: Demonstrate principle Z. Originally published in (citation), except for the section showing [some other thing].
...
and so on.
Upvotes: 0 <issue_comment>username_5: I'd say in a footnote in the title page of the chapter: "A version of this work is published as ...".
No need to cite the thesis in the paper.
In my experience, paid positions have requirements to list affiliations in anything published while you work there. PhD programs don't typically.
Upvotes: 1
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2023/08/24
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<issue_start>username_0: I am a new adjunct professor at a US university teaching calculus. I had a student complain during my first lecture and tell me that the order in which I was covering the material was wrong and that they spoke on behalf of all the students in saying that I was confusing them. They were trying to coerce me into teaching their way. So under pressure, I tried to appease them and said that I will try to accommodate the request.
But, in speaking with senior faculty, I actually had reason to cover the material my way and that it followed previous year's syllabus.
Ok, so how do I deal with this? I can't risk them complaining, otherwise my contract won't be renewed and my job is gone. But, on the other hand, I can't just simply change the whole syllabus to cater just one student.<issue_comment>username_1: First, my sympathies. Even with tenure, old gray bald head, etc., I still routinely have a few students in my grad math courses complain that I'm not doing what they expected. :) (Despite my endless explanations about my choices...)
In your situation, you should just say (to some degree correctly) that the syllabus is not your choice, etc. It's not within your power to change it. That is, you are "just the messenger", and that the complainers can only change things if they persuade "your bosses" [sic].
That is, plead helplessness. Of course, in bad situations, that's potentially unethical and/or immoral, but with regard to syllabi for math courses, it's not usually that bad. :)
True, your students may still be unhappy after you've said it's not within your power to change things... but, perhaps you can attempt to explain "on scientific grounds" why the syllabus is reasonable, at least as a good-faith demonstration.
Sigh. Good luck. :)
Btw, it was even more "hilarious" decades ago, when it was not really feasible to create typeset notes, etc., ... and authors of books were inarguable "authorities". (Note the etymology...) Back then, having a textbook for a (grad) course (in Minnesota, unlike perhaps-fancier places) was required. It was seemingly not possible to disagree even with mere *conventions* in the official text, no matter what the mathematical explanation/justification. The *most* hilarious things were "definitions", especially regarding things that in reality do not have universal definitions... and, duh, anyway, are just conventions, to explain what we mean when we say a thing.
My point (apart from some potential entertainment value) is that it's an uphill battle to explain to people (even grad students) that some things are just conventions, that there's no sacred logical order, and so on. So, first, don't be surprised. Second, if you're in a junior/vulnerable position, try to pass off responsibility (even for sensible choices) to "your boss(es)".
Upvotes: 5 <issue_comment>username_2: Have you explained to them why you cover materials in certain order? Maybe they cannot see the big picture or you failed to explain how some materials have to be explained first before they get to some other materials. It is OK to have your own way but it needs to be justified. Otherwise, you will come across as incompetent.
Upvotes: 2 <issue_comment>username_3: >
> I had a student complain during my first lecture and tell me that the order in which I was covering the material was wrong
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I would recommend being polite, but firm.
* Start with a simple explanation ("we cover limits before derivatives because limits are needed for the definition of the derivative"). Try not to be defensive, just treat it like you're answering a genuine question.
* If that fails, simply state that your course covers the topics in a certain order, and there is good reason for that, though it may be different from what you expected. The trick is to say it politely and calmly but firmly; do not give the impression that the matter is open to debate.
* If that fails, become even firmer. "I don't have anything further to say on this matter, let's get back to the lecture."
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> I can't risk them complaining, otherwise my contract won't be renewed and my job is gone.
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One student complaining is unlikely to be much of a problem.
* If you have deeper problems (e.g., if the students generally think your lectures are incomprehensible and disorganized), then this incident is a symptom of that and you are likely to continue to have problems regardless of how you handle this incident.
* But if things are generally fine and this student is just being obnoxious, then one student is unlikely to derail things. Trying to appease obnoxious students is a losing game; you are likely to lose the respect of other students without even achieving the respect of the obnoxious student.
Upvotes: 5 <issue_comment>username_4: The first obvious thing to check is that you are actually teaching things in the best possible order. It takes a lot of courage to admit being wrong, especially in front of students, and when one is in a position of authority. It's my opinion that one of the worst things a lecturer can do is lean on their authority to save face, e.g. "It might be wrong, but it's my way!" I still remember the college professors who pulled that, and still hate them for it.
You said that you checked with your colleagues and you are justified in doing things the way you do them for pedagogical reasons (the fact that last year's syllabus did it one way is no reason; the syllabus can be wrong two years in a row.) So I'll assume that you are correct.
To teach effectively, one needs to adopt the difficult position of the benevolent dictator. You need to create an environment where students feel free to question you about anything and everything, and this is OK, because being the expert in the room, you should have an answer to everything and anything they throw at you. Even if the answer is "that is outside of the scope of the class, but if you come to my office hours we can talk about it." So when a student claims that they know a better way to teach the class, you just need to calmly explain why you are teaching it this way, and how it is to their benefit. Then you move on. I'm going to call BS on any student who says they are talking on behalf of the class -- they are just the loud ones, and if your explanation is reasonable, most students will silently agree with you.
Back to the benevolent dictator metaphor, part of your responsibility is also to keep order in the class. Some students, usually early in the semester, try to poke holes in your authority, and if you let them there's no way to get your authority back. They'll go to the chair of the department, and then to the dean and then to the provost over the smallest of grading disagreements. And being an adjunct, there's a risk that somewhere along the chain of command someone will say "this guy/gal is too much trouble, don't renew the contract." So paradoxically, to keep your job you have to be stern, especially at the start of the semester, establishing your authority.
Just to be on the safe side, you can go by the chair of the department and check with them if they agree why you are teaching in that particular order. Something along the lines of "I am OK with teaching it either way, but I think this way is best for the students because of this. What do you think?" When that student, the one complaining in your classroom, inevitably goes to the chair to complain, they'll get their ass thrown to the hallway, and you've re-established your authority in the classroom.
There's always a risk that the department will not back you up, but it's also impossible to teach without authority. Students can't run the classroom. I once taught as an adjunct, and a student kept not showing up for exams and then demanding a make-up. I let it happen once (thus undermining my own authority), and then the student kept demanding it for every subsequent exam. When I tried to stand my ground, the student went on to complain up the chain of command. I knew they were complaining, but I never heard anything from the department other than my contract was not renewed. I took two lessons out of this: (1) I did this to myself by undermining my own authority early in the semester (breaking my own rule of no make-ups unless you're at the hospital) and (2) I don't want to work at a department where they don't back up their adjuncts.
Upvotes: 4 <issue_comment>username_5: Of course, as a starter, you should respond professionally and consider their comment seriously. Explain the general pattern of the course and why it makes sense, and inform them of the department's requirements of you to teach it in this order in any case. Reading your question and the comments you've left, it seems like you did all of this.
If the student continued to complain, then I would remind them that they've only been in the class for 20 minutes and that they need to give it a chance and if they've got concerns at the end of the class you're happy to continue the conversation. At some point for practical reasons you've got to keep the class moving, and you can't allow one person to derail the course. (I don't know if this person kept complaining or if it was a one time thing, that would really change how this went.) If they're continually wasting class time trying to coach you, then you're going to have issues with students doing poorly simply because they've lost instructional time to Karen or Darren.
Beyond this, there are some questions you've got to consider. Why is this student taking calculus if they already know the subject well enough to complain about your order of topics in the first lecture? Presumably they've taken a calculus course and done poorly, which doesn't really speak well for their understanding of the topic in the first place and perhaps implies that the order that they were expecting was less than effective.
In my experience a problem that many students fall into is trying to learn algorithmically - particularly those students for whom the class is not in their area of interest (ex: a chemistry student who has to take calculus). They want to learn how to do one problem and then copy their method to every other problem directly by looking at an example. If they are presented with another method for solving a problem they will often reject it regardless of its quality simply because it is new. You can sometimes talk to these people and try to get them to change their outlook to wanting to understand how the subject matter works on a deeper level so that they're not trying and failing to cut and paste.
Good luck, try not to get discouraged. Teaching does get easier with practice.
Upvotes: 2 <issue_comment>username_6: As I wrote in the selected answer to [this related question](https://academia.stackexchange.com/questions/151379/how-to-deal-with-unruly-unengaged-students-who-complain-about-me):
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> **This is the kiss of death.** It's a common mistake for first-time teachers. I made the same mistake in my first semester.
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As I observed in that other answer, you've given the signal that you're a pushover, and as a result all of the students will be expecting to push you around every day all semester, about everything (lecture content, assignments, due dates, grades, etc.). You've put blood in the water while surrounded by a bunch of sharks.
This is already a situation that will be very difficult to correct! At least you have the advantage over the prior querent that you're asking this after one day, instead at the end of the semester. Your only option now is to reject any further complaints or requests for dispensation firmly (even harshly).
Upvotes: 3 <issue_comment>username_7: This student's complaint doesn't make sense on several levels:
* Why would a student think they are in a position to tell the instructor what order materials should be taught?
* How could a student claim, after only half of a single lecture, to be speaking for the entire rest of the class?
My first instinct is that your student is a troublemaker, and my internal response was not worth reproducing here.
But after reflection: Maybe there is an issue with the prerequisites for the class. Since this is a class where the syllabus has been developed in advance by the department, it seems unlikely that the problem is on the university end. But maybe there's been some error somewhere and the student lacks mastery (or even exposure to) some key material for the class.
It would be a kindness to help the student rule that out, especially early enough in a term for them to do something about it.
Upvotes: 3 <issue_comment>username_8: You listen to the complaint. You don't believe for one second his claim that he is "speaking for all students". You think about his complaint. Is he right or is he wrong? If you are teaching things in the wrong order, then you change the order. If according to your best judgement you are teaching things in the right order, then you keep that order unchanged. You tell the student that you thought about his complaint, and in your professional opinion the order is correct and will remain unchanged.
Hopefully that is the end of it. You don't need to justify yourself to this student. He has an opinion, which is based on listening to half a lecture. You have an opinion based on studying the subject for a long time. Your opinion counts more for two reasons: First, because you have more justification for your opinion. Second, because it is you who has to do the extra work if you make a change, not him. If he continues complaining then you may suggest that maybe he should take this course elsewhere.
Upvotes: 3 <issue_comment>username_9: As a student, I've never felt the need to criticise a lecturer in this way, as if I disagreed with the way the material was presented or found presentation skills incompetent, I would resort to self-study which was my preferred method anyway.
While there may be some malicious or arrogant motivation to the student's criticism, I think it's worth ascertaining if they are genuinely struggling and what the source of that is. Assuming it's an introductory calculus class and they've come straight from school for example, it may be the case they haven't been adequately prepared.
I would try to reframe the student's objections to them, so they stop seeing it as a "the lecturer needs to change" problem and instead an issue of them potentially needing some initial additional support with the course. I don't know how your university handles that but in my BSc years I had a sort of supervisor that was a member of faculty that I'd see once a week in a small group (our 'tutor' in the UK) that was available to answer questions in that session and during office hours.
Upvotes: 1 <issue_comment>username_10: I actually had a similar situation when I was teaching in the US in 2011. I was teaching a class from a syllabus prepared by the faculty, but it was an introductory calculus class in which we were supposed to teach concepts from real analysis (e.g. semi-rigorous limits) that were way too difficult for students at precalculus level.
The students were very upset with me and started complaining to the other faculty. For example, I asked the question "If two functions have the same graph, are they the same function?" in an assignment, and the students showed it to various other faculty members, who said they were not sure of the answer.
Eventually, driven by complaining students, the head of department came and sat in on the class to find out what was going so wrong. I never found out, because he didn't really have any constructive criticism for me, except for a few minor things.
In the end, I think it might just come down to the students not liking being taught confusing stuff by a foreigner. But I don't know, because some of my other classes ran really well.
Anyway, my point is that offering to have a senior faculty member sit in on your teaching might be a good strategy (not after class one obviously, but if things continue to deteriorate. And they probably will! Once you are, in the terminology of <NAME>, a "shot-rolling ship", there is not likely to be any going back. My ratings for the class were terrible, but I remained in the faculty's good books.)
Upvotes: 1
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2023/08/25
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<issue_start>username_0: My group leader was supposed to give an invited presentation (all expenses paid) at a conference halfway around the world. Due to personal reasons he can't go (more or less last minute, the event is in a month) and has asked me to give the presentation for him, the conference organizers are happy with this switch.
The issue is, this would be the longest flight I ever took in my life. I don't like flying and I personally try avoid flying whenever possible due to the impact of flying on climate change. I am torn, as this is quite the opportunity (I am still a PhD student) and that my group leader chose me as the replacement instead of other more senior colleagues, on the other hand I think it is insane to fly halfway around the world for a presentation that takes 1 hour.
Is it ok to say no to such an offer and explain why I do not want to go, or will this be carreer suicide? What is the best and most diplomatic way to decline without causing too much damage? Or should I rather bite the bullet and just go?<issue_comment>username_1: The problem with this type of opportunity is that you can't predict the outcome. It could be that you receive great applause after your presentation, and then someone approaches you with a job offer (this actually happened to me!) Or it could be that you attend, give your talk, nobody talks to you throughout the conference, and it turns out to be an absolute waste of time (this has happened to me more times than I can count). And then the Earth's climate is a bit warmer because of you.
I will argue that the critical piece of information in your question is that you are a PhD student. You need all the contacts you can get, and all the exposure you can get. The person who suggested you as replacement will owe you a solid one. The conference organizers will thank you. If there's a banquet, they might seat you with the big wigs. And you are at the stage where you need to get your ideas in front of as many people as possible.
If you decide to decline the invitation, however, it won't be career suicide. The reasons you were invited in the first place will remain to be true. And the Earth will thank you.
Upvotes: 6 <issue_comment>username_2: You might look at the consequences of your action.
If you refuse because you have objections to flying as such: someone else will have to go and nothing has changed.
If you refuse because you are afraid of flying and being in another country: You should honor your feelings, but also consider to overcome them by just doing it. But at least you have a reason that your advisor can accept.
If you refuse on general grounds: You might be missing out on opportunities to learn and to interact with others. You might be loosing out on making connections that last for your whole professional career. (I speak from experience.) Also, there is a reason that conferences are still the primary way of disseminating ideas in CS: enough happens at conferences to justify the personal costs of the attendees (and the financial costs to who-ever has to bear them).
If you refuse: Your group lead has made a commitment and your group needs to honor it. You were selected for a reason. Maybe your lead sees this as an opportunity to "put you on the market", or to allow you to "start making contacts", or to introduce you to the world of science. Your refusal will put you at least temporarily into the category of "difficult Ph.D. students".
If you do not refuse: At worst, you have a few days of traveling and feeling out of your safe zone. At best, you learn better how the scientific world works, you are exposed to new ideas, you have the chance to make contacts, especially with other Ph.D. students, you make a valuable contribution to your group's work, ...
Upvotes: 2 <issue_comment>username_3: >
> I personally try avoid flying whenever possible due to the impact of flying on climate change. [...] I think it is insane to fly halfway around the world for a presentation that takes 1 hour.
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I think this is an odd opinion for a researcher to have about their own group's work. Surely the reason you are doing research at all is because you think there is enough value in it?
Consider how much effort and resources went into the research project which culminated in this conference submission. Perhaps a few researchers spent a few weeks each on it, which means that bright minds were focused on that project rather than something else; and other costs may have been incurred. If it's insane to fly halfway around the world to present the results, is it not also insane to *do the research that produced those results* in order to present them? After all, submitting the results to an international conference was presumably the end-goal of this project from its inception.
You're probably thinking at this point that the paper containing the same results will be published in the conference proceedings, and people can read that paper whether or not you present at the conference. But the number of people who will ever read that paper, is probably at best similar to the number who would see your presentation; and certainly more people will read it if you present than if you don't.
So telling your group leader that you would rather not present for this reason, is essentially saying that you think presenting this work would have less value for the world than the cost of one plane journey's worth of CO2. Not only should you not say that to your group leader (it would be incredibly rude!), but if you really believe it, then it seems like you should have a much bigger decision to make about your work than just whether to present at this one conference. Is there some other research you could be doing instead, that *would* be worth presenting?
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Consider this analogy: suppose Amy is tasked with driving across town to deliver a book to Bob, and Amy declines because driving will cause CO2 emissions. Without judging Amy for her decision, we still must conclude that Amy thinks the value of Bob receiving that book is less than the CO2 cost of one car journey.
This is not a cost-benefit analysis, and I'm not saying Amy should or shouldn't deliver the book. Rather I'm saying if she decides not to for this reason, then that reveals that she does not value Bob getting the book that much.
Now suppose that Amy is *the author* of that book! To me, there is an obvious question: if Amy doesn't think the book is worth delivering to a reader, why did she think it was worth writing and getting printed? Not only is the cost of creating the book much greater than the CO2 cost of delivering it, but the value of creating it depends on it being delivered.
And again, I'm not saying that Amy *should* think the book she wrote is valuable, nor am I prescribing what action Amy should take. I'm saying it seems like Amy has deeper things to figure out than just whether to make this one delivery to Bob.
Upvotes: 3 <issue_comment>username_4: I understand your dilemma, but you'd be making a mistake to refuse that, and would look very bad, internationally. Thus, a big negative right even before having a career. Now, let's explore why is that. You said that you were selected instead of more senior colleagues, right? So this means that your group leader has FAITH in you. Now, do you want to disappoint him/her solely on the fact of "the impact of flying on climate change"? And what about the impact of that presentation? Sorry, but you sound selfish here...
You know, among the most hated people on this planet are those taking integrity to an extreme. Those people, generally, don't bring anything good to the table and are a nuisance. On the other end, those with very low, if not none at all, integrity are the worst of the worst ones. It's all about BALANCE. Also, as said above, what would be the impact on your lecture? That impact could very much offset the negative impact on planet Earth. The positive impact could be global, or affecting those present who in turn will do better in life, and/or even help you to get a better career, therefore to do more good in the future.
This being said, there are also circumstances where it's a total waste of time and energy but since you didn't tell anyone what that conference is about, and no other relevant info, then we can't say much.
Last, many would see it negatively that a young person working on his/her Ph.D. is refusing an opportunity and honor like that. Thus, closing many doors in the future. But, again, you avoided telling us what it is, so it could be a good thing to refuse something shady, and totally worthless. If so, refusing would make you look good.
Bottom line, based on the little info you gave us, refusing based on your reasons would have a serious negative impact, besides making you look selfish and narrow-minded. Everything is about perception and one with no audience or despised can't do much good... Think about Cousteau. He gained fame in order to get the necessary funding for the ocean's exploration, and got ocean awareness to an international awareness. Yep, he spent tons of fossil fuel traveling and with his boat, but the gains were much higher than the negatives. Having had your non-productive and narrow-minded attitude nothing of that would have been possible. And what about <NAME>? Do you think he's traveling the world on foot and swimming to bring awareness and good things to planet Earth?
Upvotes: 2 <issue_comment>username_5: Oh boy, is there a lot of cynicism in the comments ...
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> Is it ok to say no to such an offer and explain why I do not want to go, or will this be carreer suicide?
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First off, saying no to one specific conference invitation is certainly not "career suicide". Opportunities come and go, and all of us sometimes (or rather: quite frequently) need to leave some opportunities on the wayside because of circumstances. So if you feel particularly bad about **this specific conference** then just say no and go on with your life. Sure, just maybe this would have been the transformative event for your young career, but much more likely it would have been like most conferences - mildly interesting, but not something very different to the dozens of other conferences you have or will attend.
That said, saying no to **all** international conference invitations **will** be a severe hinderance (unless academia radically changes in the next years). I understand your concerns, and they are definitely valid, but right now academia is a reputation game, and not attending conferences would be a disadvantage you likely can't afford. We all like to believe that our journal papers will speak for themselves, but my slightly cynic observation is that they do not, if the competition also has good journal papers and travels around the world to advertise them.
So the question I would ask myself is: is this conference much worse than other conferences in terms of climate impact? For example, if you live in the US and the conference is in Australia this may be the case - there will be plenty of high-profile conferences that you could attend instead, some of which you can take the train to. However, if you live in Australia, almost *any* (international) conference will be "halfway around the world", and, quite frankly, you will need to come to terms with the idea of going to such meetings once or twice a year.
One way not to reduce the climate impact, but to make it more "worth it", is to combine your long international travel with other activities. For example, if you already go around the world you can take the opportunity to travel, have a nice vacation, or visit other universities. When I was a PhD student, I travelled to a lot for conferences, but I never went on a plane *just* to take a vacation (and even now, 10+ years later, my desire to take a long flight just to see a place is limited since I have visited most places that interest me after a conference).
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> What is the best and most diplomatic way to decline without causing too much damage?
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If your group leader is sympathetic to your climate concerns you can just tell them. If not, I would make up some other reason (concurrent obligations, some family commitment, etc.). As you can see from the comments, the sad reality is that some people will get *really* upset if you bring up climate concerns, and start questioning your commitment to academia. If you are unsure I would probably make up a white lie.
Upvotes: 4 <issue_comment>username_6: As apparently some people seriously believe that not going could amount to "career suicide", let me add to what has already been posted by saying that I am not aware of any single case in academia in which anything even remotely similar to the decision discussed here has come up as an argument when it came to admission decisions, and neither have I ever seen anything like this mentioned in reference letters. So I don't think there is any hard evidence that such a decision has ever had any direct negative impact (other than opportunity cost) on anyone's career.
Of course this doesn't exclude the possibility that such a decision may make a bad impression on somebody influential, which can have an informal impact, although I don't have evidence of this either from talking privately to scientists (admittedly some discussion comments here could be seen as constituting such evidence). Still, I am far from convinced that *just the decision to be made now* will have any negative impact at any more than negligible probability on career prospects other than simply missing anything positive that could come out of going there.
Upvotes: 1
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2023/08/25
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<issue_start>username_0: There are a couple of studies in which I don't agree with the analysis methods but the authors have graciously made the data available.
I'm considering working on some re-analyses of these studies using this publicly-available data. Broadly the structure of these papers is to
1. discuss issues in the original analysis,
2. propose statistical and causal analysis methods that remedy those issues,
3. run the analysis,
4. compare and contrast to the original analysis and
5. discuss the new implications on domain knowledge due to the improved analysis (if any).
Some of the titles are already quite long, so prepending something like "Re-Analysis of """ seems horribly-verbose. Indeed, any naming method that prepends something to the original title is going to have this problem.
How should I go about titling papers that are essentially a direct response to the methods of a particular study?<issue_comment>username_1: Depending on the extent and type of analysis you intend to perform, you could consider the term "secondary data analysis". In the medical field it is not uncommon.
Upvotes: 1 <issue_comment>username_2: In my opinion, you should focus on points 4 and 5 first, since they are the important parts of your work. If you perform the analysis and your get significantly improved results, then thats what you should make clear with your title, so perhaps something more in line of "Improved analysis of [Problem]"
If you title the paper as "Re-analysis of [paper title]" then (to me at least) it sounds like you simply re-analysed an existing work, and made little contribution to the field. It would downplay the intended role of improving the state of the art.
A response to a paper could be different, if you simply wish to point out something you consider to be an error, as opposed to a less accurate analysis, then you may title the paper as you outlined, including the original paper title.
Upvotes: 1 <issue_comment>username_3: Two years ago, I published a paper that was largely a re-analysis of some of my own prior data, plus some additional data not previously published as we tried to understand the conflicts between the other data sets. The title didn't emerge until late in the process, but ultimately focused on the comparison that we performed: ["Comparative analysis of three studies measuring fluorescence from engineered bacterial genetic constructs"](https://doi.org/10.1371/journal.pone.0252263)
I would likewise advise you to not worry about the title until you know what you have actually learned from your re-analysis:
* If you learn something novel and interesting, that will be the focus of your title, e.g., "Circadian patterns in mosquito flight trajectories." The fact that it came from somebody else's data is a mere detail for explanation in your background and methods sections.
* If you learn nothing interesting beside the fact that original work is flawed, you might not be publishing on your own, but instead be writing a "comment" article that urges a correction or retraction.
* If it turns out the original article was sloppy in a way that turns out not to be very interesting or to significant affect its conclusions, you might not find it worth publishing anything at all, [unless it's a pattern in the field](https://doi.org/10.1093/scan/nsp053). In that case, your title will be about the pattern, not the individual papers, e.g., "Bayesian statistics produce misleading conclusions about mosquito flight trajectories."
Note that in all cases, the title depends on the results that you get, so you shouldn't worry about it until you finish your analysis. Once you have learned from your analysis, your title should tell your reader about what you have learned.
Upvotes: 4 [selected_answer]
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2023/08/26
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<issue_start>username_0: I need to get the LOC call number of multiple ebooks.
I used to use <http://classify.oclc.org/>, but now the website doesn't seem to work anymore.
Is there a (freely accessible) platform, database, dataset, or API that allows user to retrieve a LOC call number for a book?
By the way, I have tried using university library catalogues, and the Library of Congress catalog, but, especially with ebooks, the data does not have the LOC call number.
An example of a title is:
Atlas of Male Infertility Microsurgery<issue_comment>username_1: I was able to find my own (print) book, published in August, 2023 in <https://www.worldcat.org/>, but apparently you need a paid subscription to see the call number. *However,* WorldCat does list libraries that have a book, and you can sometimes find the call number by checking the entry of a particular library. I found *Atlas of Male Infertility Microsurgery* in WorldCat, but was unable to find a record with a LOC call number. (One of the libraries with this book lists the call number as "R1.")
The Library of Congress no longer attempts to catalog "everything," and unless a copyright registration is submitted, probably doesn't even know about most material, especially self-published material. The cataloging in publication (CIP) data in most books comes from catalogers who either work for publishers or provide a paid service to small publishers and individuals. For that reason, not every publication will even have a LOC call number.
**Update:** I found this note at the MiraCosta College Library's web site: "Keep in mind that only physical items, not electronic ones, will have call numbers."
Upvotes: 1 <issue_comment>username_2: try librarything.com i don't know how big that database is but I was able to find call #s there
Upvotes: 0
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2023/08/26
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<issue_start>username_0: While learning mathematics, I found "Hilbert spaces", "Vieta's Formulas", and "Cauchy Equation." My question is what is the rule for using "Mike's Theorem" and "Mike Theorem"?
Why are there not "Hilbert's spaces", "Vieta Formulas" and "Cauchy's Equation"?<issue_comment>username_1: In theory (see below) it would be the possessive only if the person that developed the theory on their own also, possibly, named it after themself. While Hilbert, for example, was an early developer of the concept, the name *Hilbert Space* was applied to it by von Neumann. And, Hilbert wasn't the only early explorer of this world. Perhaps that last is the key. The name is in some sense an honorific due to the work of a great mathematician.
On the other hand, *Fermat's Last Theorem* was clearly Fermat's work and his alone, though I don't know the history of applying the name.
So, if Mike alone develops a theory and names it, then it is Mike's Theorem but if Mary names it after Mike and she and Mike developed it, then she would (in theory, again) name it the Mike Theorem.
However, in theory, Theory is the same as Practice, but not in practice. So, don't expect consistency.
An anecdote in math is that Hilbert had to ask someone else, possibly von Neumann, but I don't remember: "What is this Hilbert Space thing, anyway?"
Upvotes: 4 <issue_comment>username_2: There probably isn't a single reason, and I certainly don't disagree with username_1's (+1), but I think part of it may be whether it describes a single thing or a set of things. "Hilbert space" doesn't describe a single space, it is a set of mathematical spaces that have a common property:
>
> [A Hilbert space is a real or complex inner product space that is also a complete metric space with respect to the distance function induced by the inner product.](https://en.wikipedia.org/wiki/Hilbert_space)
>
>
>
If we were to write "Hilbert's space" it would imply a specific space, rather than a set of different spaces, so it would be awkward to write "a Hilbert's space". We could say "a Thompson's gazelle", but in that case we are treating "Thomson's gazelle" as specifying a specific species (and the differences between particular examples are irrelevant).
Unfortunately English is very irregular and I suspect a lot of it is down to whether something "sounds" right when you say it (and as a result it evolves substantially over time). A lot of students these days say "based off" rather than "based on", which sounds awkward to me (a generational thing?). I can see the logic of "based off" as it generally means something that departs from its base concept. Which is right? These days, both are "right" because both are in common usage.
Upvotes: 2 <issue_comment>username_3: I agree with what username_1 and Dikran say, but I also think one can be more precise about typical usages.
* [possessive usage] Use when a theorem etc is due to someone. It need not indicate uniquely defined result. E.g. [Cauchy's inequality](https://en.wikipedia.org/wiki/Cauchy%27s_inequality) or [Wedderburn's theorem](https://en.wikipedia.org/wiki/Wedderburn%27s_theorem) can refer to multiple results, determined by context. It is also bit awkward to use the possessive form if there multiple names--who says Taniyama-Shimura(-Weil)'s conjecture?
* [adjectival usage] Usually only used if it specifies a relatively well-established and unique result etc. Also preferred if there are multiple names, e.g., the [Cauchy-Schwartz inequality](https://en.wikipedia.org/wiki/Cauchy%E2%80%93Schwarz_inequality) or the Taniyama-Shimura conjecture. If needed, another adjective can be added to ensure unique specification, e.g., "the Big Picard Theorem." (Don't say "the Picard theorem", but "Picard's theorem" is okay in context.)
That said, sometimes it is just author/speaker preference, and may depend on the surrounding grammar or minor nuances. E.g., sometimes I'll write "Langlands' Conjectures", and sometimes "the Langlands Conjectures", though at least for me there is a bit of sense when I use the latter that I am referring to a *specific* and *precise* set of conjectures.
Upvotes: 3 <issue_comment>username_4: Great insights in the other answers. I just thought I'd mention an ancillary thing that is worth bearing in mind: According to [Stigler's law of eponymy](https://en.wikipedia.org/wiki/Stigler%27s_law_of_eponymy), Mike's theorem may actually have been discovered by John.
Upvotes: 2
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2023/08/26
| 451
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<issue_start>username_0: I have a question regarding the submission process on arXiv. I previously submitted a paper and now I would like to update it using the "replace" feature. **However, despite attempting this process twice, my requests have not been executed and the paper remains unchanged.** I'm wondering what the best course of action is in this situation. Should I contact a specific department regarding this issue?
Any guidance or advice would be greatly appreciated. Thank you in advance for your help!<issue_comment>username_1: If the submission is disappearing at the end of the expiration date, the most likely scenario is that your submission has never been fully submitted for replacement.
The first thing you should do is [contact arXiv via the support channel](http://arxiv.org/support/general_help) with the submission-id from any one of the replacements you've begun. If you no longer have them, you can reach out with the arXiv-id and we can check to see what's occurred to the individual replacements you're referring to. Without that information it's very difficult to be specific regarding what the problem is, but this basically boils down to one of two potential problems:
1. You haven't completed the replacement and your submissions are expiring; or:
2. You've completed your replacement, it's actually gone out and your browser is reloading the page from its cache.
[From our help pages](https://info.arxiv.org/help/replace.html): Replacements after number 5 should not be made more frequently than once per week. Versions ≤4 will appear in the mailings in the replacements section.
Upvotes: 3 <issue_comment>username_2: There is a submit button on the very last page (which you can only click once you downloaded the submission, either on this page or earlier after processing the latex sources). While this page looks like a final page, its point is to give you a last chance to (double-)check the submission before finally submitting it. Only once you click this submit button, the submission is actually submitted.
Upvotes: 3 [selected_answer]
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2023/08/27
| 392
| 1,786
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<issue_start>username_0: Submission systems like ScholarOne or Editorial Manager have options where one can indicate absence / unavailability periods. In what context are these options useful and do you make use of them?<issue_comment>username_1: If the submission is disappearing at the end of the expiration date, the most likely scenario is that your submission has never been fully submitted for replacement.
The first thing you should do is [contact arXiv via the support channel](http://arxiv.org/support/general_help) with the submission-id from any one of the replacements you've begun. If you no longer have them, you can reach out with the arXiv-id and we can check to see what's occurred to the individual replacements you're referring to. Without that information it's very difficult to be specific regarding what the problem is, but this basically boils down to one of two potential problems:
1. You haven't completed the replacement and your submissions are expiring; or:
2. You've completed your replacement, it's actually gone out and your browser is reloading the page from its cache.
[From our help pages](https://info.arxiv.org/help/replace.html): Replacements after number 5 should not be made more frequently than once per week. Versions ≤4 will appear in the mailings in the replacements section.
Upvotes: 3 <issue_comment>username_2: There is a submit button on the very last page (which you can only click once you downloaded the submission, either on this page or earlier after processing the latex sources). While this page looks like a final page, its point is to give you a last chance to (double-)check the submission before finally submitting it. Only once you click this submit button, the submission is actually submitted.
Upvotes: 3 [selected_answer]
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2023/08/27
| 2,676
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<issue_start>username_0: I got admitted to Peter the Great St.Petersburg Polytechnic University, for a bachelor's in physics. I am starting this fall and it'll take around 4 years to graduate.
It'd be good to do the right things early, from the beginning. I want to have a clear roadmap of what you have to do right now, in order to get admitted into a US graduate school.
Of course, the top HYMPS colleges, etc. are really attractive, but I am open to all options out there in America.
I am not really sure If I should go into a master's studies or start pursuing a Ph.D. right after undergraduate school. Does getting a master’s degree improve the chances of being accepted into a Ph.D. program, or, perhaps, would it be a positive addition to my CV/ Resume for employment purposes?
If it does, is it important that the master’s degree has the same direction as the desired Ph.D.? For example, would it be okay to have a master's in Engineering and a Ph.D. in physics?
From what I know, probably a few things are needed in order to be accepted as an international student at a US grad school:
* High undergrad GPA (3.8 out of 4 or higher)
* High GRE score. Is it still relevant, though?
* Concise and meaningful application essay. Describe exactly what you want to do. Explain why you are applying there. Explain the specific details of the school that would contribute to your mission/goal positively.
* Solid scientific publications record
* Affinity for the school. Really know the college. Laboratories, professors, etc. At least be aware of them.
* Letters of recommendation from known professors and people in the field would be a boost to the application
* Clean social media profile
* I have also heard from a few interviews [[1]](https://www.youtube.com/watch?v=ctHQ3OSAyK4), [[2]](https://www.youtube.com/watch?v=x2fBwH6CupA), that it is good to present your ideas for research and experiments in the application.
I am interested in Quantum, Condensed matter, Nuclear physics
Also interested in Molecular biology and Biochemistry
However, I am ready to focus on one direction.
At the same time as studying, I'd like to earn money on a part-time job/freelancing/business.
I've accepted the fact that I am going to work/study all the time, for 15 hours or plus a day, every day.
What do you have to do to achieve acceptance to a US Ph.D. in physics as an International student? I'd be glad if you could suggest a roadmap/way to do this.<issue_comment>username_1: First of all, congratulations on your admission to St. Petersburg Polytechnic University! You can't pursue a Ph.D. without an undergrad education, so you are about to take the first important step!
I intend to write a detailed response later, but a few tips for now, stemming from personal experience:
1. Use American textbooks when you study for your classes or at least try. It'll help you learn the English jargon and also understand how the American education system works
2. Find a mentor, if possible. A professor, a senior student, a post-doc, or anyone who can provide guidance with respect to graduate studies. This person will usually be related to a research direction you choose so their role might be dual (research advisor and mentor)
3. Engage in research projects whenever you feel ready, don't rush into things. Do something you like. If you like it, you'll do a good job, and recommendation letters will follow (and perhaps publications)
4. GRE and TOEFL, were vital when I applied, but you should check the current requirements
5. Network. Network. Network. Connect with peers aiming for U.S. studies. Sharing experiences helps, and being around like-minded individuals grows the right mindset
6. The more I grow up the more I add this item. Please enjoy the process and have fun
Upvotes: 4 [selected_answer]<issue_comment>username_2: I can offer some answers to your specific questions based on my own experience from about a decade ago. Things may have changed somewhat since then, but probably not too much. (Also bear in mind that this is only one person's perspective and that requirements can vary from one university to another.)
>
> I am not really sure If I should go into a master's studies or start pursuing a Ph.D. right after undergraduate school. Does getting a master’s degree improve the chances of being accepted into a Ph.D. program, or, perhaps, would it be a positive addition to my CV/ Resume for employment purposes?
>
>
>
In the US it's typical to go directly from a bachelor's degree program into a PhD program, with no intervening master's degree. The first couple years of a US PhD program are often pretty similar to a master's degree program: you take classes and do some amount of educational research, like a literature review rather than a truly novel research project. (Of course you can also be working with a professor on some original research on the side.) If you do get a master's degree and it is in the same subject (i.e. physics), you might be able to skip those first couple years, but this depends on the university.
>
> * High undergrad GPA (3.8 out of 4 or higher)
>
>
>
Most graduate programs do not have a strict cutoff on what undergrad GPA you need to get admitted, and for those that do, it's certainly not going to be as high as 3.8 (except maybe at a few of the most exclusive schools, but even then I kind of doubt it). If you do have a GPA of 3.8 or higher, then that's fantastic, but even if it's as low as, say, 3.3, you'll probably still have a good chance of admission to many PhD programs in the US as long as the rest of your application is reasonably strong. The expectation here also depends on the reputation of your undergraduate university: if you go to a rigorous school which has a reputation for turning out well-prepared students, then you can get away with a lower GPA than if you go to a school whose standards are loose. I don't know offhand how Peter the Great St. Petersburg Polytechnic University fares in that respect, but based on some quick research it seems to be reasonably well regarded academically so that probably helps you.
Also note that your "major GPA" - that is, the average grade from among classes relevant to your major, i.e. physics, math, maybe computer science or engineering if you want to specialize in an area of research where those are relevant - is probably more important here than your overall GPA.
>
> * High GRE score. Is it still relevant, though?
>
>
>
The general GRE (verbal and math) don't really matter. However, the subject GRE in physics does matter. It's similar to GPA in that there is probably not a strict cutoff, but a high score will be impressive, while a moderate score will not be a deal-breaker if the rest of your application is strong.
>
> * Concise and meaningful application essay. Describe exactly what you want to do. Explain why you are applying there. Explain the specific details of the school that would contribute to your mission/goal positively.
>
>
>
I'm really not an expert on application essays but this all sounds pretty good. :-)
>
> * Solid scientific publications record
>
>
>
This is not necessary at all. If you have publications, that's great and will certainly be a major benefit to your application, but as far as I know, the majority of incoming graduate students at US universities do not.
>
> * Affinity for the school. Really know the college. Laboratories, professors, etc. At least be aware of them.
>
>
>
Again, not necessary.
Knowing a professor helps though. Specifically, if you've worked with or communicated with a professor at the university you're applying to, enough that the professor is willing to advocate for you to be admitted so you can work with them, then that will be *extremely* useful. This is one thing I wish I had known about graduate admissions when I went through the process: it goes better if you treat it more like applying to a job with a specific research group rather than applying to a university. But if you don't have that, no need to panic, it is certainly possible to get admitted without it and find a professor to work with after you enroll. (I did!)
>
> * Letters of recommendation from known professors and people in the field would be a boost to the application
>
>
>
Yes, absolutely.
>
> * Clean social media profile
>
>
>
This really doesn't matter at all. If there's anything extremely offensive on your social media then it *might* disqualify you, but it's also possible nobody will check.
At least, back when I got into grad school it would have been nearly unthinkable to take social media into account when considering applications to grad school. Maybe things are a bit stricter now.
>
> I have also heard from a few interviews [...] that it is good to present your ideas for research and experiments in the application.
>
>
>
Yeah, probably true. Like many other things I've listed here, I don't think it's necessary, but it will help if your ideas are good.
---
One other thing I happened to notice while looking up information on your undergrad university: the [Wikipedia article](https://en.wikipedia.org/wiki/Peter_the_Great_St._Petersburg_Polytechnic_University#Current_status) says
>
> During the 2022 Russian invasion of Ukraine, the University issued a public statement strongly supporting Russian actions, calling the assault a "denazification operation" and accusing Ukrainian leadership of endangering the security and existence of Russia and "all of humanity". According to <NAME>, head of the university, while scientific cooperation with Western universities had been developed over decades, after the invasion it was almost completely destroyed, with foreign universities halting their ties with the university.
>
>
>
Now, I don't know exactly what "halting ties" entails, but it's possible that US universities are declining to admit graduate students from Russia right now, and especially from Russian universities which have supported Russia's position in the war. If that's the case, then all your other preparation may be wasted. However, it's also possible that the political scene will look very different in four years; if the war ends and there are some significant changes in the position of the Russian government and Russian university leadership, then I can imaging US universities might relax any restrictions they may currently have. So this is not a reason to give up hope. I just wanted to point it out because it's an important factor to be aware of.
Upvotes: 3
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2023/08/27
| 934
| 3,854
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<issue_start>username_0: There is a certain rule that if your PhD degree is more than 6–7 years old, you cannot apply for a postdoc position.
Suppose a physically and mentally 100% fit 70-year-old person obtained his PhD degree in 1996 from Southeast Asia. He then worked as a teacher in two tertiary public institutions for 21 years, and he is now retired from public service.
Now he wants to get involved in academic research again in the EU.
How can he do that? Can he get paid for the research?<issue_comment>username_1: There are places where post-docs are reserved for recent graduates and aren't open to older, more experienced, people. There are exceptions, I suspect, but it would be a hard case to make.
If you can't get a regular position at some university, there is the possibility that you could teach as an adjunct (low pay, few benefits) but use the contact to get yourself involved with the full-time faculty and connect to their research.
I've known people to do this in the US, but, for them, money wasn't an object, since they had regular positions. But they used the adjunct relationship just as I suggest and were considered part of the community. Not a lot of people like this, but a few.
But, being retired, you may be secure enough financially to make something like this work.
Upvotes: 3 <issue_comment>username_2: I think the 'getting paid' part is close to impossible. At age 70 in the EU the general assumption is that you are retired. Getting any regular paid work contract will be very difficult and come with legal hurdles.
If you care more about getting involved with research this sounds a lot more feasible. As a start lectures and advanced seminars are usually open to the public (sometime you can get a kind of 'no-degree student id' that lets you attend these). This allows you to learn about the current research and get to know the professors. From there you can try to get involved in some joint research projects if you can convince the professors you have something useful to contribute.
Upvotes: 3 <issue_comment>username_3: I've not seen the 6-7 years after PhD to say you can never get funded. That time limit usually applies for certain fellowships or certain grants/funding sources, and even then there is usually simply a different level of funding to apply for rather than prohibiting getting any funding.
But still, post-docs that's are funded by the University/professor's grants usually wouldn't have this limit. There may also be a limit that you can't be on a temporary contract (i.e. already being a post-doc) for more than X years at the same place/country.
I would double-check the wording of the limit, at the very least it's not a common limit so there are likely other places you could do a post-doc that would not have that limit. However, you may need to move further away to do so.
Your best chance is simply to reach out to people who are interested in working with you. Maybe they can give you a "different" job title to avoid the limits or they would know of other schemes you could apply for.
Upvotes: 2 <issue_comment>username_4: Yes he can, but not the direct way.
Such an experienced person can be a great advisor or consultant.
Such a person may be lucky enough to get a guest position in some university (unpaid, but with access to library and all the infrastructure).
I think that this person need to invest a remarkable amount of time in marketing themselves as a possible supporter of PhD/Master student (even as a private tutor), and then they will get possibly some network of contacts (1 to 10% of PhDs will be at least assistant professors in the 5 years after graduation ... ). By the age of 80 this person may have some of his previous contact in a soild, stable academic position: then he/she can discuss about contributing to a research project.
Upvotes: -1
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2023/08/27
| 2,741
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<issue_start>username_0: I keep hearing from Americans that on average, private universities tend to be better than public ones.
[This study](https://journals.sagepub.com/doi/full/10.1177/0022057419875124) by Klafke et al. concludes:
>
> A recurrent problem reported by the students, especially by the public undergraduate, is the disconnect between what is taught and the practical reality of the job market. This can happen because students from private colleges are eyeing the market. If they wanted to enter the academic life, they would have to migrate to the public tuition, where research is encouraged.
>
>
> Public undergraduates consider some professors lazy, self-centred, and
> selfish, as they are very rarely fired. This damages not only the
> quality of the learning-teaching process, but their relationship
> itself.
>
>
>
On the other hand, [this study](https://www.sciencedirect.com/science/article/pii/S2212567116000812/pdf?md5=d595a6c90dd61a29da3e677ec4ec69d6&pid=1-s2.0-S2212567116000812-main.pdf&_valck=1) points in a different direction.
[This study](https://link.springer.com/article/10.1007/s40797-015-0022-7#Abs1) compared the efficiency of Italian public and private universities, and found that private ones are more efficient.
Here's one of the results:
[table](https://i.stack.imgur.com/1rHvD.png)
Despite the fact that in Italy (like in Europe and East Asia) the best universities are public, whereas America has both private and public top universities.
Is there any other metric we could use for comparison? What do you think?<issue_comment>username_1: Different strokes for different folks. It depends on what you mean by "better". Different students have different desires and the US provides a wide range of possibilities. This answer applies to the US, only so far as I know.
Most public research universities are very good. Many private universities are very good. But they are different. The research possibilities are probably better, in general, at public universities, but the undergraduate classes tend to be very large with not a lot of contact with professors (more with TAs). Private universities tend to have smaller classes, maybe 30 or so, with more contact and personal attention possible.
At any university, the education is what you make of it. Yes, you can get a wonderful undergraduate education at Yale, but not everyone does. There are some very foolish US politicians who spew garbage but have degrees from Ivy League universities. It has been said (apocryphal, perhaps) that there is no one dumber than a C student from Yale. And, BTW, The Ivy League is an athletic conference.
The excellent private research universities are often old and have "deep pockets" provided in part by contributions from wealthy alumni over the many many years. They can afford to hire great faculty, and often do. And, due their age, a reputation can build on past accomplishments. But public universities have the backing of state taxpayers who, at least in the more enlightened states, value an educated populace - for many reasons.
At public research universities, in the final year or two, students have more opportunity for close contact with a research focused faculty member. This can be important for some, but not all, students.
My undergraduate years were at a very good private place that, at the time, had only about 2000 students. Classes were small. Faculty was focused on teaching. I never thought a lot about research in those years so it didn't matter to me that my professors weren't primarily researchers.
My graduate years were at good public universities where I was a TA. Classes were large and I, as a TA, handled most of the student contact, rather than the professor. Graduate classes, however, were small.
The fact that some might consider faculty at a public to be "lazy, etc." doesn't make it true. They are busy, but with research, not with student contact, for the most part.
Note, however, that the US also has a lot of smaller public universities that value teaching over research. The university systems in both New York and Minnesota, for example, have smaller teaching focused colleges, much like the typical private university. Costs are a bit less (for residents) than private places.
I live in a town with a public teaching-focused university. My neighbor told me that the expectations for faculty advancement there depended on contributions to teaching, research, and service at a 60/30/10 ratio IIRC (or close to that). Reverse the first two numbers, more or less, for a research university.
The US has thousands of colleges and universities. They range in quality from terrible to excellent.
Upvotes: 5 <issue_comment>username_2: For that type of analysis, one should probably group universities into **three** categories, rather than two:
1. Public universities.
2. Private not-for-profit universities.
3. Private for-profit universities.
I would strongly advocate that the results for private not-for-profit and for-profit organizations would differ a lot for many reasonable "efficiency metrics" ([maybe relevant](https://academia.stackexchange.com/q/87957/56594)).
Regarding metrics themselves. I believe that there cannot be a universal approach. And some aspects of university "effectiveness" are more quantifiable than others, and it is hard to put the weights on different contributing factors (like what is more important: average salary of graduates after 2 years/10 years or number of papers published or satisfaction of students measured by surveys).
There are multiple schools of thought on how to measure it (and whether to measure it at all), and I would start with ["Performance measurement in universities" by <NAME>](https://doi.org/10.1016/0377-2217(89)90012-X), following the references of this paper and other papers that cite it. Ultimately, in my opinion, the value of finding a perfect metric is essentially flawed due to [Goodhart's law](https://en.wikipedia.org/wiki/Goodhart%27s_law):
>
> Every measure which becomes a target becomes a bad measure.
>
>
>
...but that does not mean that we should not try to evaluate and measure things, constantly changing the methodology and goals (while still retaining as much raw data as possible).
Upvotes: 4 <issue_comment>username_3: Here's the situation in my contry (Mexico); a lot of people brag when their children (aged from 6 to 15 years old) attend a private school instead of a public one, arguing that private education is of higher quality, that they teach English and other language, and that kids on the public system are "poor and nacos" (yes, it is a shameful, racist, but sadly widespread belief), but we all know that studying in a private college is way worst than attending a public one. Even the kids from private institutions take the admission exams to attend a public college (the spaces available to study there are limited, so usually [a high percentage of students fail to find a place](https://www.jornada.com.mx/notas/2023/07/22/politica/quedan-fuera-casi-90-de-aspirantes-a-licenciatura-de-la-unam/#:%7E:text=S%C3%B3lo%2010.5%20por%20ciento%20de,180%20mil%20166%20fueron%20rechazados.)). The problem with private colleges is that their fees are ridiculously high, and the courses they give are a joke compared to the ones offered by public ones (see for example the [weird curriculum of a data science bachelor's](https://tec.mx/es/ciencias-aplicadas/ingeniero-en-ciencia-de-datos-y-matematicas) offered by <NAME>, the most expensive Mexican college. They don't even have calculus nor probability courses. Contrast it with the [curriculum offered by UNAM](https://www.fciencias.unam.mx/estudiar-en-ciencias/estudios/licenciaturas/maplicadas)). You can check out this [ranking of universities in Mexico](https://www.usnews.com/education/best-global-universities/mexico); as you can see, most of them are "autonomas" (that usually mean they are public). So, in general, a private college is the second, less attractive option.
Talking about how valuable is the degree obtained to get a job in real life, of course the graduates from the expensive places (like Tec de Monterrey) have it easier to get the administrative/managerial job posts (remember the nasty "poor and naco" stigma), but they are generally not well prepared for jobs relating to health sciences or STEM (indeed, you can see that private colleges focus on careers like law, business administration or accounting, it is rare to see careers like chemistry or physics).
Personally, I attended public schools all my life, I can't deny it has **a lot** of deficiencies, but I can also say that my peers that were before in a private place were in general slower for learning stuff by themselves, wanted the exams to be an exact copy of the homework, prioritized memorizing over understanding, and think that the teacher/professor is one of their daddy's employees, so they tend to be dismissive and insolent.
Upvotes: 3 <issue_comment>username_4: >
> I keep hearing from Americans that on average, private universities tend to better than public.
>
>
>
I am surprised to hear this. Rather than judging the assertion itself, it may be helpful to understand the likely causes of the assertion:
* The most famous, very top undergraduate programs are indeed private. For example: the entire Ivy League (which includes Harvard, Yale, Princeton), MIT, CalTech, Stanford. Of the public schools, only Berkeley regularly appears in the top 10.
* At the *secondary* level (high school), private schools are widely considered better (in reality, this is certainly true in some areas, dubious in others).
Given these two things, it is easy to assume that private is better than public as a general rule. But it is hard to make general statements. Berkeley (public) is in an entirely different class than Hillsdale College (private). To do an apples-to-apples comparison, you have to control for many different variables. It's probably more productive to consider your personal options and goals rather than trying to get a general answer.
Upvotes: 4
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2023/08/27
| 1,105
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<issue_start>username_0: I am a grad student in the life sciences. I have to mentor several undergrad students. One student in particular is just so bad and is always getting confused with protocols. He can't follow a protocol from start to finish without getting help from me or others, even if he has done it multiple times. I'm having to spend several hours babysitting him when he has to do simple procedures, even after nine months in the lab. I've often had to stay behind until 8 p.m. to catch up on my own work. He is utterly dependent on me, to the point where I feel suffocated.
I'm fed up. What can I do?<issue_comment>username_1: We all forget too quickly how it felt when we didn't know how to work in the lab. Others treated us like stupid, when just had not yet learned the skills. If you become a professor, you will end up spending a big part of your life just training people who don't know how to do things. And the older and more experienced you get, the harder it becomes to remember how it feels to be on that first step. So yes, you are training the other person, but you also need to train yourself in the art of training others.
With that out of the way: nine months is an awful amount of time, and what you are supposed to do is *training* not babysitting. Either the student develops independence, or they find someone at a lower level who can supervise them, for example, a more experienced undergraduate. By rejecting them from your supervision, you are not condemning them to lower-level status or ruining their career, but telling them that there are skills they need to learn before they can work under the supervision of a graduate student.
How did you end up with this student? Did you ask for undergrads to help you, and you hired this one? Then you can also fire them. Did your advisor assign this person to you, as part of research money the advisor is getting? Then talk to your advisor about reassigning the student, perhaps to a two-undergraduate team where this student reports to an undergraduate, an that second undergraduate then reports to you (or another grad student.)
Upvotes: 5 <issue_comment>username_2: Undergrads are often under-committed and overloaded with coursework. They want to experience research due to an idealized notion of what it is and are then overwhelmed by what is actually being asked of them.
It’s perhaps not too late to have a meeting where you manage expectations. How many hours/week are they devoting to the project? What are they good at? What can they expect from you in terms of mentoring? It’s useful to have a written “contract” (could be just an email summary). Some labs even have students sign those, to lend them more weight, though I personally don’t. Mentoring plans are super important in my opinion.
If you both see that you have widely disparate opinions about your work relationship, you should definitely contact your PI and let them know.
Upvotes: 3 <issue_comment>username_3: On top of what others have said, remember that one of the best ways people learn is by being made to do it themselves. There's no problem with telling someone to figure it out on their own *after* you've given them appropriate scaffolding. In fact, you might be making them codependent if you make yourself too available.
Tell the student you're leaving at 5:00 PM (or whatever is appropriate for you) and they need to have it done by then. Or if this is the kind of lab where you can leave the undergrads on their own, tell them you're going home and they need to finish themselves. Even if you have to be in the lab, tell them you're doing your own work and unavailable to help them that day. Even if they break stuff and waste lab supplies, they're also wasting money by taking up your time as a grad student or faculty (and arguably a lot more, because salary is not cheap).
Our rule of thumb is that undergrads should work on a problem for 10-20 hours before bothering the grad students about it. Grad students should work on a problem for even longer before bothering their advisor about it.
If they don't get anything done because they spend a week mastering simple procedures... well... that's undergrad research for you.
Upvotes: 3 <issue_comment>username_4: username_3 mentioned setting boundaries, I want to add that setting expectations is also important.
I often have a talk with them beforehand letting them know how I will be annoyingly micro managing the first few times I teach the protocol. I expect detailed notes, then I will shadow the next few times also expect annoying nagging. Then I expect the student come to me with questions, and don't be afraid to let them fail.
Upvotes: 1
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2023/08/27
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<issue_start>username_0: We found out that a graduate student coworker was hiding materials and even throwing them away when they realised they might get caught.
With this they were not only stealing but also actively stopping others from doing experiments (materials worth 500 $ – 1000 $). When we approached them, they were first lying and gaslighting a lot (“How can you think that of me?”, etc.). The next day, when they realised that the last remaining person is also a witness, they suddenly cried, apologised and asked for forgiveness. They said it was because of personal problems.
My gut tells me that the PI deserves and needs to know this, and I have a hard time being silent on this. Other people involved want to give them a second chance.
Any thoughts what to do?<issue_comment>username_1: #### Escalate to your PI or the relevant ethics officer
This is quite a serious situation that involves both loss of university resources and also hampering multiple researchers from their learning/research activities. For those reasons, I recommend that you escalate this either to your PI or to the relevant ethics officer for your faculty. The matter can then proceed according to the standard university protocols for dealing with student misbehaviour, and any mitigating factors will be taken into account. You and your fellow students can make your own decisions re forgiveness while this process is dealing with the matter, but you should not seek to substitute yourselves as arbiters of the matter.
Upvotes: 6 <issue_comment>username_2: **Is the person stealing, or keeping a secret stash?** There's a big difference. The difference might not be obvious as both types of behaviors prevent access to materials. But there is a difference, especially in the context of a lab.
For example, in wet labs, there's a system of stock solutions vs. working solutions. The stock solution is kept on a separate area where everybody has access to it, and there is an expectation that everybody be extra careful not to contaminate or mishandle the container (e.g. leave it outside if it belongs in the fridge, expose it to light, etc.) Problems arise when the lab does not have a good system of restocking the stock solutions, or where not everybody is careful regarding cross-contamination and handling issues. In these cases, people tend to keep a secret stash of stock solution, just to make sure they have access to materials when it's time to do particular experiments. Everybody keeping a secret stash brings about a host of new problems, like added costs, solutions expiring, and more. But the problem is not that lab personnel are being evil and "stealing" the stock solution, but bad lab management.
So from your comment,
>
> We found out that our coworker was hiding materials and even throwing them away when they realised they might get caught.
>
>
>
This sounds like keeping a stash, and then panicking when caught and trying to get rid of the evidence, perhaps because keeping a stash is not allowed by lab rules, while the underlying issues have not being fixed. And according to comments by the OP, the discarded materials were a few uL in an otherwise used tube. And $500-$1,000 worth of materials can fit in a 50uL microcentrifuge tube, so the amount itself is not surprising. Before going too far with the accusation, I'd make sure others are not doing the same thing.
You also need to be careful with how you present your accusations. Even if the OP has other information that would make this actual "stealing", getting caught stealing is quite an embarrassing situation, which can spill into overwhelming feelings of shame. In a lab situation, where people work together with shared resources for years at a time, it can make the perp feel overwhelmed (e.g. "everyone knows I'm a thief and treats me like one"), which can end up in serious stuff, like suicide. This is not a far-fetched idea, and it's the reason we professors, when catching a student cheating, we are careful to refer to the student as "someone who was caught cheating" as opposed to "a cheater." The first describes a reversible situation (the student can accept the consequences and stop cheating), the second describes the character, the being, of the person and is a judgement on that person.
Whatever the facts, you have to tell someone up the chain of command of the incident. Even if the lab is well managed and what this person did is inexcusable, everyone deserves a second chance. But it's not your job to administer discipline in the lab, it's your supervisor's job. They have to decide if this is an isolated incident. And if it's the first time, it needs to be put on file so that the second time counts as the second time. If it's the second, third, or fourth time, then the supervisor needs to know so that they can refer the student to the next person up the chain. It also gives a chance to the supervisor to learn about the possible underlying problems, like issues with keeping enough stock materials for everyone to do their experiments.
Upvotes: 5 <issue_comment>username_3: I strongly recommend to escalate this for the following reasons:
* If you do not escalate, this partially becomes your responsibility, too, i.e., if your supervisor or the university find out, they might consider you partially responsible for the loss of materials. This particularly applies if the behaviour continues.
* Seriously consider how things would unfold if you do not escalate and the problems continue. If any material vanishes in the future, your coworker will automatically be the suspect and drama may ensue, which may affect further relationships in your group. If your coworker gets caught again and you escalate then, it may still only be a first offense and as mentioned in the previous point, you may get blamed too. This may even prevent other coworkers from escalating thus perpetuating the situation.
* Even just going by your description, your coworker already got their second chance. It’s not that they stole something once and happened to get caught. They acted multiple times and only happened to be caught now.
* Your PI may be aware of more offenses and aggravating factors than you and your colleagues. This may already be the second or third chance. Avoiding escalation at all costs is a common tactic for certain people to leave no paper trail and stay under the radar. This is exacerbated by the lying and gaslighting you describe: They apparently have the skills to avoid problems and the ethical flexibility to use them. They only performed remorse once the other tactics failed.
* Due to several of the points above, escalating is more likely to actually end the behaviour. If your coworker is as manipulating as you depict them, they may be well aware of all this.
* You and your colleagues might be worried about ruining your coworker’s career, and this may indeed be the effect of escalating. However, consider that there are probably fewer academic positions than people interested in them in your field. Thus if your coworker gets their next position, this will inevitably end somebody else’s academic career – just that you don’t know this other person.
Upvotes: 5 <issue_comment>username_4: As others have pointed out, this is a potentially serious situation. You have no idea how deep the problem goes, how long it's been going on, or really anything beyond what you've observed. Further, how would you feel if one of your colleagues reported it when you choose not to. How would you answer the question "why didn't YOU say something?"?
Of primary importance to the PI will be issues surrounding data integrity. When the PI hears of the problem, they will probably want to confirm that all the data generated by the lab is real and confirmable. If it's not, and you do nothing to call this problem to the attention of the PI, you may find yourself in a situation that you don't want to be in.
My recommendation would be to
* Keep personal contemporary notes on everything having to do with this issue. Maybe make sure they're time stamped. You might consider emailing your notes to yourself -- though I don't necessarily recommend creating an electronic data trail that way because email may not be confidential, and it may not be the best thing to write down accusations in a way that could turn up on somebody's desk without you knowing it.
* Contact the PI about it in a way that you can trace. For example, send an email to the PI that says "I'd like to meet with you to discuss a delicate and potentially important situation". CC yourself. Save a copy of the email with your contemporaneous notes. This way.
* If the PI is amenable, meet with the PI and tell them pretty much exactly what you've posted here. After the meeting, summarize it in your contemporaneous notes. If the PI is not amenable to the meeting, write that down in your contemporaneous notes (though I can't imagine that the PI would treat this that way).
This way, you're reporting an adverse situation to the immediate supervisor without skipping any organizational levels. You will not have done this in a way with potential security risks. You can trace the conversation in a convincing way if you ever need to (for example, if the PI chooses to ignore the situation and data integrity issues pop up later). After these actions, even if the PI chooses to do nothing, you've met all of your responsibilities in this situation, and can prove it.
Upvotes: 2 <issue_comment>username_5: ### Forgiveness does not imply forgetting/hiding
Forgiveness is only meaningful and worthy if the person to be forgiven truly attempts to make amends for the (moral) error. In almost all cases, it is not at all enough to say "I am sorry". So a moral analysis of your situation already tells you that you cannot just ignore the whole thing. He stole, and he has to make some kind of recompense before he can be justly forgiven. And this is impossible unless the crime is reported to someone who can handle the problem. Your PI is one such person.
It is also very disturbing that others involved want to give them a second chance. For all you know, this problem may run deeper than you think, and it is not your responsibility to dig, but merely to report to the appropriate authorities. Why do I say "disturbing"? Because gaslighting in order to evade capture is really really immoral and harmful to you and other victims. If you do not do what you can to permanently stop this, there will be more victims.
Upvotes: 1
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<issue_start>username_0: I submitted a paper to an international conference, but the registration fees were initially undetermined. Once the list of accepted papers was published, the conference website provided information about the registration fees with some reductions offered for participants from low-income countries. However, two weeks later, the registration details were unexpectedly changed, and no reduction is now available. This situation has left me unable to participate, even though I had already committed to preparing and submitting my camera-ready paper based on the previous registration information.
Given these circumstances, I am contemplating whether it would be appropriate to communicate with the conference editors to request a reinstatement of the reduction option.<issue_comment>username_1: Yes, given all the circumstances you list it would be perfectly reasonable and proper to ask for a reduction.
The change in rules was either an accident or, sadly, evidence that something is wrong. Are you sure that it is reputable and respected? If not, you might consider withdrawing your paper.
I'd also worry, at least a bit, if they make no accommodation.
Upvotes: 4 <issue_comment>username_2: In computer science, conference often offer financial support to folks in your situation. There should be an option to contact the conference chairs, you should tell them exactly what you wrote here - especially that your plans relied on an initial written promise for financial support.
Conferences also sometimes have student volunteer/doctoral mentoring programs that offer your discounts on registration in exchange for sitting at a booth and handing out badges (you get a free T-shirt too!).
Contacting your university and asking if they can help is also an option.
Finally, some organizations offer travel grants (e.g. the NSF offers travel grants on a first-come first-serve basis, and some professional organizations such as ACM or IEEE offer ad-hoc support).
If you cannot get funding, contact the chairs and ask if participation is a necessary condition for paper acceptance. It may be possible that they will allow you to present remotely, or ask you to find someone who will present your work in your absence. Both aren't great choices, but are probably the best in your circumstances.
Good luck!
Upvotes: 3
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2023/08/29
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<issue_start>username_0: I am currently a PhD student (international) at a University in the US (TX). I was offered a TA position, however the position requires me to work as an instructor of the course. I worked before as well with a similar opportunity.
Being an instructor I have more work responsibilities compared to only being a TA. But for the instructor work I get paid the same as what I used to get for a TA.
Is this correct? If not, what should I do from my end as I feel this is unfair? I talked about this with my research advisor but he was not very helpful.<issue_comment>username_1: If graduate students at your institution have no union, you are out of luck. You can ask for more money, but as long as there's a line of people waiting behind you to teach for the same low pay, the university administration can just say no. Now, if all of you got together and refused to do extra work for no extra pay, the university would have to listen. That's what unions are for.
This is not to say that you should not ask. You should. A close friend of mine works at HR (pharma), and she tells me that they have employees side-by-side doing the same job making vastly different salaries. The difference is that one asked for more money, the other did not. So ask. What I am warning you is that over a long career in academia, I have never seen a graduate student successfully negotiate a higher salary, outside of a union context that is. I have even tried to negotiate on behalf of my students, and failed.
As in any negotiation, it boils down to leverage. The university has students to teach, and money in the bank. You have the ability to refuse to teach. If money is more scarce to you than TAs are to them, you lose. If you don't really need the money and they have a hard time finding TAs, you might be able to pry a salary increase from them. But don't count on it. At most universities, administrators will rather cancel a class than raise a salary.
On the merits of your argument, that being an instructor is more work than TAing, I'd say "it depends." When I was a grad student, I had to TA for a professor who pretty much abandoned the class to me, and that included lecturing, writing and grading exams, preparing labs from scratch, making and grading lab exams, etc. When I was an instructor for a lecture-only (ie no lab) course, the only work was to prep the lectures and grade the exams I wrote. So a lot less work. Since most institutions have non-negotiable TA rates (again, without unions), the battle among graduate students moves to who's teaching which class, as everybody wants the classes with a low workload.
Upvotes: 3 <issue_comment>username_2: Every time you are offered a job, you should ask for more pay. If you are unionized, read the contract first to see what you are allowed to ask for. Otherwise, find out what the market rate is and ask for a bit more than that.
Since you specified this is the United States, I can say that [this answer](https://academia.stackexchange.com/a/201230/13240)
has several inaccuracies.
First, in the United States, employees do not need a union to bargain collectively. You can organize the other employees "waiting in line behind you" and request higher pay as a group.
Second, depending on your individual situation, it's not certain anyone else can do the job.
Third, while administration probably will say no to an increase in pay, they might say yes. You would need to find the right person to ask.
I should also add: Some universities claim, implausibly, that graduate students are not employees and are not protected by labor law. There has been litigation about this in the past few years. Public universities are governed by different laws from private universities.
I think it is unfair for instructors and TAs to be paid the same amount. I think your university will agree. Universities care about supply and demand. They care about negotiating leverage. But they also care about fairness and their reputation for fairness. I do not know if they will fix unfair pay, but asking for more pay is in your interest. If you do not want the work, refuse it.
Upvotes: 4
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2023/08/29
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<issue_start>username_0: A while back I co-authored a commentary with a colleague. I would now like to write an original article/paper, as a sole author, based on the commentary I co-authored. Basically, I want to extend the ideas presented in the commentary. Do I need my colleague's permission to do so?
If I do need their permission and they decline, what recourse do I have?<issue_comment>username_1: If graduate students at your institution have no union, you are out of luck. You can ask for more money, but as long as there's a line of people waiting behind you to teach for the same low pay, the university administration can just say no. Now, if all of you got together and refused to do extra work for no extra pay, the university would have to listen. That's what unions are for.
This is not to say that you should not ask. You should. A close friend of mine works at HR (pharma), and she tells me that they have employees side-by-side doing the same job making vastly different salaries. The difference is that one asked for more money, the other did not. So ask. What I am warning you is that over a long career in academia, I have never seen a graduate student successfully negotiate a higher salary, outside of a union context that is. I have even tried to negotiate on behalf of my students, and failed.
As in any negotiation, it boils down to leverage. The university has students to teach, and money in the bank. You have the ability to refuse to teach. If money is more scarce to you than TAs are to them, you lose. If you don't really need the money and they have a hard time finding TAs, you might be able to pry a salary increase from them. But don't count on it. At most universities, administrators will rather cancel a class than raise a salary.
On the merits of your argument, that being an instructor is more work than TAing, I'd say "it depends." When I was a grad student, I had to TA for a professor who pretty much abandoned the class to me, and that included lecturing, writing and grading exams, preparing labs from scratch, making and grading lab exams, etc. When I was an instructor for a lecture-only (ie no lab) course, the only work was to prep the lectures and grade the exams I wrote. So a lot less work. Since most institutions have non-negotiable TA rates (again, without unions), the battle among graduate students moves to who's teaching which class, as everybody wants the classes with a low workload.
Upvotes: 3 <issue_comment>username_2: Every time you are offered a job, you should ask for more pay. If you are unionized, read the contract first to see what you are allowed to ask for. Otherwise, find out what the market rate is and ask for a bit more than that.
Since you specified this is the United States, I can say that [this answer](https://academia.stackexchange.com/a/201230/13240)
has several inaccuracies.
First, in the United States, employees do not need a union to bargain collectively. You can organize the other employees "waiting in line behind you" and request higher pay as a group.
Second, depending on your individual situation, it's not certain anyone else can do the job.
Third, while administration probably will say no to an increase in pay, they might say yes. You would need to find the right person to ask.
I should also add: Some universities claim, implausibly, that graduate students are not employees and are not protected by labor law. There has been litigation about this in the past few years. Public universities are governed by different laws from private universities.
I think it is unfair for instructors and TAs to be paid the same amount. I think your university will agree. Universities care about supply and demand. They care about negotiating leverage. But they also care about fairness and their reputation for fairness. I do not know if they will fix unfair pay, but asking for more pay is in your interest. If you do not want the work, refuse it.
Upvotes: 4
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2023/08/29
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<issue_start>username_0: I am a postdoc in (applied) math. I have completed one year and have two years left on my contract. I want to stay in academia, so I'm trying to decide whether to apply for tenure track jobs this year. There is one department I am particularly interested in, and it is my understanding that they will be hiring both cycles (although who can be sure?). It seems there are two possibilities:
1. Apply this year (and next year if rejected)
2. Apply next year
Obviously my CV will be longer next year, but presumably applications are also judged with some regards to where you are in your career.
What are situations in which applying next year is preferable to applying this year? And does the choice depend much on whether or not the department would reconsider an unsuccessful application the next year (i.e. if I have to apply in just one cycle)?
---
I know there are a number of questions/answers about [when to apply](https://academia.stackexchange.com/questions/70996/when-to-apply-for-permanent-positions-while-having-a-lengthy-postdoc) for tenure track jobs, with the overall goal being to land a job *somewhere*. However, the answers don't seem particularly relevant to the situation of trying to get one a specific job.<issue_comment>username_1: You should apply both this year and next year. So many reasons:
1. The university might decide on not opening the second faculty line. This might happen up to the day before the expected announcement.
2. You have some control over your CV, but no control over the CVs of your competition. Dr. Superstar might not apply on the 1st year but then apply on the 2nd year.
3. Luck. Your stars might align on the first year, e.g. they want someone like you, a candidate better than you misses the deadline, your specialty is high on their list this year, but not next year if they hire someone in the area this year (from @John Custer, comments), etc.
4. You need all of the practice you can get. If you get to the interview stage, even if you don't get the job you'll get valuable experience. There's nothing like a real interview to help you self-assess.
5. A job now is worth 2 jobs "maybe later."
Upvotes: 6 [selected_answer]<issue_comment>username_2: Since you seem concerned about whether applying the first year will affect the second, I thought I would write an answer addressing that directly: I really don't think you should worry about this. I mean, I can't completely rule it out, but I think any danger is far outweighed by the advantages. Certainly, you wouldn't be rejected the second time purely based on the first time; no one would be keeping track, and as people have noted, there's no guarantee that the committee is the same people (usually there will be some overlap, but not exactly the same composition). It is at least as likely that you'd make a negative impression by *not* applying since it could be taken as a sign you're not interested in the job.
I think a general theme around the job market is that applicants worry too much about getting rejected over technicalities (since this definitely can happen at some other stages of life). That's not how hiring committees think. They want to hire the best person for the job (in their own opinion of course, which is a big caveat), and if they think that you are that person, they aren't going to worry about technicalities.
So, if you want to be hired for a given job, apply for it. Don't make it any more complicated than that.
Upvotes: 2 <issue_comment>username_3: Choosing a person that fits a position is always a combination of two things: the applicant and the position open. The selection comitee is not only "ranking" the applicants, it is also judging how good they will fit in the required position.
Although you are almost the same now and in one year from now, the position may be more adapt to you now than in one year.
Upvotes: 0
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<issue_start>username_0: I am a third-year computer engineering student at a university in Croatia.
In 2020, my Computer Architecture professor asked me to make an assembler and an emulator for PicoBlaze that would run in any modern browser. In return, he would excuse me from the assembly language exam (meaning he would give me an A, even if I didn't show up for the test) and let me write my Bachelor thesis about that project. I did that, and you can see the work [on my website](https://flatassembler.github.io/PicoBlaze/PicoBlaze.html).
A few months after I made the PicoBlaze assembler and emulator, I had some mental health issues preventing me from attending the university and working on that project for almost a year. Not long before my absence, I added the MIT license to my project.
In the meantime, my work began being used at a university in Argentina for introduction to embedded systems. Recently, I received pull requests from a GitHub user named *agustiza*, who claims to be from the university in Argentina where my project is being used. At first, the pull requests were small bug-fixes, but soon they expanded with *agustiza* adding significant new features. I accepted those pull requests.
Can I still present my PicoBlaze assembler and emulator as my Bachelor thesis, or will I run into problems because a part of it was written by *agustiza*? Do I need to write a new Bachelor thesis?<issue_comment>username_1: First, congratulations! The code you wrote for your bachelor's thesis was **useful enough that other people used it to teach classes at a university level and added new features.** This is a major positive point for the impact of your work and you should be proud to say it in your thesis. Not very many bachelor's thesis code projects are ever touched by anyone other than the author.
Generally, the rule in academia is that you can use other people's stuff as long as you cite it and make it clear what was their work and what was your work. **Plagiarism** is presenting someone else's work as your own. So you don't have to worry about plagiarism as long as you are clear that others (such as GitHub user agustiza) contributed to the code.
**Copyright** is a legal issue and handled by the license that you chose for the GitHub project. This is mostly irrelevant to the bachelor's thesis as the thesis will presumably be a document, written by you, describing how you designed the code and what it does. Here you could also mention the contributions of GitHub user agustiza. The copyright of the thesis is yours and separate from the copyright of the code itself.
Upvotes: 7 <issue_comment>username_2: >
> Can I still present my PicoBlaze assembler and emulator as my Bachelor thesis, or will I run into problems because a part of it was written by agustiza? Do I need to write a new Bachelor thesis?
>
>
>
First of all, you can just choose to make a branch solely for your thesis, and without any of agustiza's changes. It's not as if anyone forced you to present those changes in your thesis. Git makes it super easy to attribute the work exactly, and to choose what commits any particular branch includes.
When presenting the project in your thesis, you can choose to use a branch with only bugfixes and no feature contributions. You'd create such a branch from some point prior to the contributions and cherry-pick them as appropriate
You should also include a "field experience" chapter that describes how the project is used by others, and what changes they made (!). There are not all that many bachelors' thesis projects that find outside users, so if anything you should be very proud!
Upvotes: 7 [selected_answer]<issue_comment>username_3: >
> Can I still present my PicoBlaze assembler and emulator as my Bachelor thesis
>
>
>
Yes absolutely. Just make sure to mention that not all code in that repository is exclusively yours and that you only write about features that you implemented as if they were your work.
Apart from that, Git blame makes it quite easy to discern who wrote what code so I wouldn't even go into the hassle of detailing that. Just write your thesis (the writing is usually more important than the code behind it anyway) and maybe add a section about collaboration (aka what they added).
If doubt still remains, talk to your supervisor or your corresponding examination office, they are the ones making the calls at the end of the day and they know how to deal with it all.
Upvotes: 3 <issue_comment>username_4: It's awesome that someone used your code and repo already. You should talk with your supervisor about this.
Any code written by you is only your work. You have to take full ownership of those parts and reason about what you did and why.
If somebody else contributed to your codebase you need to mention the author. You can not take ownership of that code. But it's your project so you still need to reason about the code that was added. And how you interact with that code. Do you agree? Do you disagree? Do you keep it?
A great way of dealing with this would be to test the code. Then you can argue the following: this is my project, this is the overall design, those parts are mine, and those were contributed by XY. To ensure quality I decided to run this set of tests. As they all passed I decided to keep this code. In those sections, you are not only an engineer but a manager of an open-source project.
If you decide to test this code make sure to test your own code in a similar way so the argument of ensuring quality holds somewhat equal over the whole codebase.
The goal of a thesis is to present the work you have done and back it up with research and evidence.
It's also great for your career, you will most likely work in teams later. You already have some experience with that in your open-source project. Not many people can say that!
Upvotes: 0
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<issue_start>username_0: I live in a third world country. I barely make ends meet so I cannot afford to go to college. However my passion for academics never died so I kept self learning with online materials. However beyond a certain level, free material is not sufficient and is hard to find so I end up relying on sci-hub and other websites. But sometimes the latest articles are not available even there so I have to search for hours in my spare time.
While sacrificing my sleep time and searching I found [a twitter post by Dr. Holly Witteman] that reads as follows:
>
> That $35 that scientific journals charge you to read a paper goes 100% to the publisher, 0% to the authors.
> If you just email us to ask for our papers, we are allowed to send them to you for free, and we will be genuinely delighted to do so.
>
>
>
This post gave me hope that I could finally get my hands on articles that I was interested in. I found emails of four writers, politely asking them for a copy of their article. However I didn't get a single reply. I tried other email services because I thought my email might be blocked by spam filters. But that didn't change anything. Eight months later I have yet to hear back. Is the practice of freely giving out papers limited to the area Dr. Holly Witteman majors in? Is this not common at all and the doctor is a generous outlier? Is it that professors are so busy that they don't respond to random people's emails?
Also why do people write for journals in the first place if they really don't make a single penny out of their work and contribute to filling the pockets of greedy publishers and more paywalls? Is publicity so important that it is worth giving up all financial incentives?<issue_comment>username_1: Yes, people do send other people free copies of their articles that are published. Authors make nothing on published papers, as the post you reference states. Often authors have a specific agreement with the journal that says they retain the rights to share individual copies of their work with people; other times they just share them, it's unlikely a journal will come after them for breach of contract unless they're very blatant about it, like posting the articles for public download rather than emailing copies to individuals.
However, that doesn't mean sending a free copy is free to the sender: it does take them time and energy to respond to an email, to dig up a copy of the PDF (remember that they may be reading email on a phone or other device), etc. The time investment may increase for older papers, and over time even papers that you've written yourself (maybe especially papers you've written yourself?) get to be stale and boring. You might also get better responses from a student who published the work than a professor who supervised it. Professors in particular get a *lot* of email. It's very easy to intend to respond to a request and then to forget about it, or to simply triage and pay attention only to the most pressing matters.
I think academics are much more likely to respond when interest is coming from someone they know or are otherwise eager to share their work with (e.g., another academic), and when the work is new. Unfortunately, your position doesn't really fit well with that mold, so you may struggle to get attention. I don't think there's much of a solution to this, being more pestering will just get you labeled as a pest. You might have better luck outside the busy and vacation times of year: summer, beginning and end of semester, key holidays, are all times when it's harder to get responses from academic emails. You might also format your email in a way that makes it easy to respond to and increases confidence that it's worth someone's time:
1. Keep it very short and to the point.
2. Identify the paper clearly, with a full citation, and make your request clear (like "can you email me a PDF of..."). If you're emailing Dr. King, "King et al 2023" might describe several papers.
3. Explain *very briefly* why the paper is important to you/convey in as short a phrase as possible that you're familiar with the field (short meaning less than a full sentence, ideally). "I'm studying Underwater Basketweaving and am not able to access full text of your paper on delicate weave morphology..." Try to sound like a human, if you copy-paste the title or something from the abstract here, you'll look like a bot.
I'm surprised you're having such trouble with the latest articles! For newer articles, the trend in publishing is tending towards open-access rather than subscription models, so it's more likely you'll find newer articles than older. Another trend in publishing is towards preprints like arXiv: these may be identical to the published article, or may be slightly different but are still suitable for your purposes. Many academics also just post .pdfs of their paywalled articles on their own personal websites, whether or not they are technically allowed to do so. Look for all these alternatives before you make a request.
Upvotes: 6 <issue_comment>username_2: This is only a supplement to the [nice answer of username_1](https://academia.stackexchange.com/a/201262/75368) who has answered all but the financial questions you ask at the end.
People publish without pay because it enhances their career and earns them advancement through the academic ranks. That comes with increased salary and also, in many cases, opportunities for grant funding for the research that leads to those papers. The benefits may not be financial, but they are definitely a benefit to a career.
Moreover, it isn't that publishers are necessarily "greedy", though some disreputable ones are. There are costs associated with publishing. Most especially for print journals, but also for online publishing in maintaining web sites and their infrastructure, with a promise of "perpetual" availability. That cost must come from somewhere since governments don't, in general, give much support to it. And, like any business, investors have a fair claim on profit, as long as it isn't exorbitant. It might seem exorbitant from someone from your location, I realize, but the costs are real.
Upvotes: 4 <issue_comment>username_3: On [Researchgate](https://www.researchgate.net/), a networking platform for academics that some do not particularly like but that I personally find useful (see other questions here on this site for more info on that), there is a feature for each added article where you can ask the researchers who put an article up there for a copy of it. They receive a notification (on researchgate) that someone asked for their research and can then easily send the PDF of the article (that they have perviously uploaded to research gate) to the asker. Sharing research is less tedious this way, but requires the person(s) you ask for their research to be logged in there every once in a while at least.
I have both received requests for my papers there and asked others for theirs and in my experience the success rate of receiving papers is quite substantial (I would say about 50%), so I would suggest to try this route. Often, you will not receive the final print version but a less well formatted draft version of papers, as this is less of an issue with copyright, but the content will be the same.
Upvotes: 4 <issue_comment>username_4: The very brief answer to this part of the question...
>
> Also why do people write for journals in the first place if they really don't make a single penny out of their work and contribute to filling the pockets of greedy publishers and more paywalls? Is publicity so important that it is worth giving up all financial incentives?
>
>
>
... is: **It's required for promotion in academia.**
Traditionally, the fundamental job description of a professor in the west is to make new research discoveries and publicize them. Teaching classes is/was considered a secondary, almost accidental part of the job.
The Chronicle of Higher Education in 2021 [wrote this](https://www.chronicle.com/article/how-do-tenure-track-professors-really-spend-their-work-time):
>
> The most common model, and the one that guides both of our careers as assistant professors, is 40/40/20 — that is, 40 percent research, 40 percent teaching, and 20 percent service.
>
>
>
Note the leading "research" component requires publication *somewhere widely recognized*. The publishers are arguably taking advantage of this need to publish with their copyright and paywall regimes. Recently many [predatory publishers](https://www.universityaffairs.ca/features/feature-article/beware-academics-getting-reeled-scam-journals/) have risen, looking to scam academics who have this occupational need to publish.
Over time (speaking USA here), as college funding has shifted proportionally from the state to students paying tuition out-of-pocket, the emphasis and proportion of time professors spend on teaching has followed the same trend (resulting in the current 40/40/20 expectation).
Upvotes: 4 <issue_comment>username_5: >
> I live in a third world country. I barely make ends meet so I cannot afford to go to college. However my passion for academics never died so I kept self learning with online materials.
>
>
>
Many academics, upon hearing this, would be more than willing to send you everything they've ever written and (if they're as junior as I am) answer questions over email. I was lucky enough to have a student from Nigeria reach out to me on Twitter and ask me a lot of interesting questions about my research and future directions for their research.
>
> This post gave me hope that I could finally get my hands on articles that I was interested in. I found emails of four writers, politely asking them for a copy of their article. However I didn't get a single reply.
>
>
>
There's two reasons for this: academic emails, and other life comitments. Many students are on academic emails which expire once their Ph.D. is done (or shortly after) so they can't be reached at that email. Another is that people are busy and there's no direct reason to do this besides a small amount of self promotion and making the world a better place, which is hard to justify against paying the bills and handling responsibilities. I would try to find an updated email for the authors and ping them again, sometimes they just don't respond when they see it the first time but showing continued interest will have them more likely to respond. Obviously, be reasonable and wait a week or two between emails.
>
> Also why do people write for journals in the first place if they really don't make a single penny out of their work and contribute to filling the pockets of greedy publishers and more paywalls? Is publicity so important that it is worth giving up all financial incentives?
>
>
>
You have to understand that many people who have the means to pursue a Ph.D. at a research university have the means to pursue something for reasons outside of money and fame. For example, at my university many people turned down jobs that would put them in the top 5% of U.S. earners to achieve personal goals as a Ph.D. student, such as furthering their research understanding or contributing to a higher scientific cause.
Upvotes: 4 <issue_comment>username_6: If you send it to multiple co-authors in one email, each one will think another will reply. If you send it to each of them separately, if multiple of them reply, you're wasting their time.
If you're sure you can't find it anywhere else, send an email to one email address at a time, waiting a few days in between each attempt. If one of them replies with the article you want, reply to everyone else you've already emailed to tell them you got it, so they don't duplicate their effort.
Upvotes: 2 <issue_comment>username_7: Some researchers put very similar (same major results described) paper somewhere where it is not difficult to find. Try just putting authors and title into Google search box.
If they have done so, they may be reluctant to respond to E-mail asking for that copy, because they think that if you need it, you should find it.
Also, write a single precise sentence why do you need the copy but otherwise do not ask for other help in the same letter and avoid contacting the same professors repeatedly. The problem is, too many people try playing on emotions so researchers tend to overreact, closing E-mail as soon as they recognize.
Upvotes: 2 <issue_comment>username_8: @vjj8919 During an [online course I did a few years back](https://www.coursera.org/learn/solar-system), [<NAME>](https://www.coursera.org/instructor/mikebrown) taught us how to use [Google Scholar](https://scholar.google.com/) (not just Google), which can help you find papers. Try this search:
<https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=life+as+we+know+it+friston>
Notice that there is a link "all 17 versions": click on it, and it will take you to a number of sites where you can find the paper. With luck some of them will not be paywalled.
Some browsers (e.g. Firefox) allow you to install a Google Scholar toolbar. If you have that you can just select the title of a paper (from another browser tab), and get Scholar to find the paper from you. I've found it very good, but YMMV.
I realize this is sketchy: let me know if you run into difficulties.
Also, many authors post preprints to [Arxiv](https://arxiv.org/). Your "<NAME>" doesn't seem to be their. I think it depends on the field: physicists and AI folk use it a lot.
Upvotes: 2 <issue_comment>username_9: One possible reason why you haven't heard back, is that some or all of the authors' email accounts aren't active any more. In modern academia, depending on the field, there's quite some coming and going in terms of personnel.
Hence, the university email of the authors of the paper might be a dead end, since they might have moved on.
Upvotes: 1
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2023/08/29
| 1,068
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<issue_start>username_0: Ever since the escalation of the war in Ukraine in 2022, numerous institutions have reacted to the event in different ways. Some cut partnerships with Russian scholars completely while others took a more sympathetic approach, arguing that most researchers do not condone the war and politics should not get in the way of academics.
I submit drafts to numerous journals, including Russian ones before the war. However until recently not a single one of them were published. Unexpectedly I received an email from a Russian journal to which I sent an article more than a year ago and forgot about. They praised the quality of my writing and asked whether I would like it to be published. On the one hand I was so happy that I finally got an offer after years of trying. However I was skeptical because that specific one wasn't outstanding in any way in my point of view. Perhaps they were running low on backlogs because foreigners stopped providing material and they had to turn to less established people like me.
I shared the news with friends and they were almost equally split on whether to go ahead with the publication or not. Half of them argued that it is a huge milestone in my career and turning it down would be a bad idea since I might not get another chance in a long time should I give up. The others warned me against the implications, who tried to persuade me to not respond and try to get it published elsewhere. They lectured me on how I could get cancelled online and be seen as "insensitive" given the current situation. They insisted that it will hit me even harder since I am an independent not enrolled to a university and thus has no institution to shield me from negative correlations.
Is it that morally unacceptable to publish in Russian journals in the Western research society? Could it really hurt my chances of being employed, being admitted to research institutions, having my paper considered in western journals and more? Are some of my friends spending too much time on social media, worrying about stuff that doesn't happen outside their online bubble?<issue_comment>username_1: I encourage you to distinguish between the Russian people and the current Russian Government. The people are, to a large degree also victims of that government.
While some, perhaps many, Russians support the government, not all do and many are in a low-information situation in which things aren't clear to them. That is probably less true for Russian academics.
I would look, first, at the historical reputation of the journal. I doubt that, in the US, at least, you would have issues with articles in reputable Russian journals unless you associate yourself, or the journal does, with current governmental policies.
The same can be said for many other nations around the world.
Upvotes: 3 <issue_comment>username_2: Not at all. It is not about Russia and Ukraine. There are disputes between other countries as well. Research has no wall in terms of geographic region. If someone tries to create a barrier it would be one of the biggest dishonesty/attack to the mankind as it could lead to barrier in the progress of scientific discovery. There were wars between countries and among countries in the past, there are cold wars in the present among several countries but there has not been spectacular barriers in the collaboration on research and communication. Political rivalry is narrow issue compared to scientific collaboration. Ofcourse, every responsible cosmopolitan doesn't support political aggression of any country, but that is another issue.
If a Russian journal is good enough (and indeed there are lots of good journals) in the specific topic, one would love to publish articles in it. If a Russian collaborator is helpful and necessary for my research, i would love to proceed positively. Research and collaboration has no geographical wall. Ultimately, the question is whether the journal is good enough or not in which your article is accepted. If the journal has good record, then you are good to go.
**Remark**: I am from mathematics. I can inform you that most of Russian journals and their publishers gave a declaration in their website on the issue of Russia-Ukrain war and the statement says it doesn't support the war. One of my article is published in a Mathematics journal in Russia. But, the same journal rejected my 2nd article for not being suitable, in 2022. So certainly "it is not like" that the journal has low backlog and therefore accepted your article as you are probably thinking about. But there might be other reasons for accepting your article, may be the referee found it suitable or maybe that specific journal is less selective.
Upvotes: -1
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2023/08/30
| 622
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<issue_start>username_0: I am 28 year old international student (Male, if it matters for the question ahead) and am about to graduate with a Masters degree in a foreign country. I want to pursue a PhD and have a few offers. But I don't think I am in the right frame of mind to do so immediately. Financially, I want to pay off my debts and also have a sufficient balance in my bank account. Personally, I feel insecure that I have never been in a relationship before and would like to settle down with someone. Also, I Everywhere I see, people are in relationships I think that I need a source of support while doing my PhD. I wanted to know everyone's thoughts about this from the people in academia. Is it a good idea to do a PhD after marriage? So far, I've heard only negative things about it but I don't think I am ready yet. Are there people who have been in happy marriages while doing a PhD? Why is it hard to do a PhD and be married? And lastly, is me letting go of my opportunity in hand, while being unmarried a bad idea? Thanks.<issue_comment>username_1: People enter graduate school unmarried and leave unmarried. They enter married and leave married. They enter single and leave married. And many also enter married and leave divorced. Graduate school is not some monastery, but just another type of job training, and like every type of training, it has its quirks.
Being married while in grad school has some benefits. To some people, it gives some structure, for example, you know you have to leave the lab/library/classroom by certain time to be home with your partner. It also brings a lot of complications. Lots of grad student partners complain that the grad student has a nice life, surrounded by interesting people, traveling to conferences, doing research that matters, while they (the partners) go to work every day and live so-so lives.
If you marry another graduate student, you might find yourself with a [two-body problem](https://en.wikipedia.org/wiki/Two-body_problem_(career)) when looking for jobs.
There are other issues which are particular to graduate school and how they affect grad students' relationships (or lack of thereof), but in general, it's just the same shit as everywhere else.
Upvotes: 3 <issue_comment>username_2: If one is married **and has young kids**, that can put a lot of pressure on one’s spouse since a PhD program can take over one’s attention, even when one is “with” the family. Both the spouse and the kids can become resentful.
Upvotes: 1
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2023/08/30
| 2,329
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<issue_start>username_0: I recently defended my master's thesis in artificial intelligence. Among other things, I invented a new algorithm that I would like to publish. The domain is natural language processing, with papers viewable for free on [ACL Anthology](https://aclanthology.org/).
For backstory: I developed my thesis almost entirely by myself. I only saw the professor who commissioned the proposal 4 times (which includes the final defence) as she resides in a different country, and although I had weekly meetings with my mentor (one of her PhD students), he was always behind on my research and hence he mainly helped with e.g. stylistic choices. I don't blame him for not having made deep contributions, since (1) it wasn't his thesis and (2) he wasn't as deep into the literature as I was throughout the year.
Now, although I included numerical experiments in my thesis, he correctly pointed out that my algorithm should be tested as part of a computationally heavy model using industry-standard metrics if I were to publish it in a paper. Being a PhD student, he has access to computational resources I don't as a mere alumnus. So, it made sense to let him collaborate on this paper.
We started a shared LaTeX document a while back, and unsurprisingly, the vast majority of all the text (intro, related work, theory, algorithm, discussion ...) will have been written by me, since I developed my thesis and hence I know both the algorithm and the literature thread that led up to it best. I also wrote all the code for my algorithm, because I needed it in my thesis. His contribution will be general remarks about the text, and providing me with the computational resources and interfaces to run large-scale experiments, so I expect that he will likely be writing that section.
I don't blame him at all for this distribution of the work; it is natural given the backstory. He's not freeloading, because his access to more, bigger experiments is a valuable addition.
---
My issue is that I want to ensure that I, a fresh graduate with zero publications, get maximal public recognition for the year-long independent work I did to reach this literary thread and this novel algorithm. *If* this paper is ever cited, it will be cited as **<NAME> (2023)**, and to be honest, it breaks my heart just seeing it that way. It is *my* brainchild. I rarely see a paper cited for its numerical experiments rather than the theoretical idea presented by it, and hence I lament that such a citation only seems to give me half the credit. That *does* feel like freeloading, even though it isn't his intention nor his fault that citations work that way. It feels like I'm selling half my credit for a single (useful and hopefully interesting) section.
He and I are are amicable, and I'd like to keep it that way. However, since my thesis was quite large (170+ pages), more than one paper can be distilled from it, and he has already made it clear that he would want co-authorship on all such papers since it is supposedly customary to give one's thesis advisor co-authorship, even though him and I both know that the content of the thesis was entirely my own doing. Whilst I respect this -- and furthermore, he did have to sit through weekly meetings with me mostly failing to articulate mathematical ideas orally -- I feel like I'm being partially robbed of making a name for myself for a unique contribution to the field. For him it seems like a closed case, and I'm not sure how to handle peddling it back. He finds my ideas valuable and has interest in them, but being interested and receiving recognition (as one of the 2 authors) are quite opposed. *What should I do?*
If he becomes co-author of these papers, then *at the very least*, I would like to somehow indicate to the reader that I was responsible for the idea and he was responsible for the experiments. Otherwise, since he already has publications, it might even seem to the reader like I am the novice freeloading off the master, and that the order of authors should secretly be reversed. *How can I handle this as neutrally as possible to the reader, and communicate my desire about this to my mentor?*
---
Perhaps I'm just insecure about lack of recognition from past experiences, or perhaps I'm insecure about possibly being a one-trick pony... but that pony still deserves proper credit for its one trick.
There is a similar thread on the site [here](https://academia.stackexchange.com/questions/121789/can-i-add-an-author-contributions-section-to-make-clear-that-i-did-all-the-wor), but quite a large emphasis is placed there in the answers on the fact that the paper has already been submitted, and also, the author is a PhD student publishing with higher-ups. In my case, the first paper has largely been written -- except for the experiments -- but has *not* been submitted for review, *and* I'm no longer a student (but might start a PhD in the near future), making my mentor moreso my colleague than my boss -- but obviously, he did have power over me when he was in charge of overseeing my thesis backed by the professor.<issue_comment>username_1: There is such a thing as the contributions section where the contribution of each other is specified. In some journals such a section is already mandatory, exactly for the purpose to provide the reader with the information which author was responsible for what.
So asking for such a section to be added to your paper is not only reasonable, but also not that unusual.
Upvotes: 3 <issue_comment>username_2: ---
tl;dr:
Remove all contributions of your co-author from your paper. What is left of your paper? no correct mathematical formalization of your idea, no testing of the algorithm, just an idea and an algorithm applying it. Treat your algorithm as an experimental apparatus. Without a rigorous formal mathematical description, you are bound to err (see [this dramatic example of how dangerous is an idea alone](https://kottke.org/19/02/flat-earther-proves-in-simple-experiment-that-the-earth-is-round)).
---
>
> My issue is that I want to ensure that I, a fresh graduate with zero
> publications, get maximal public recognition for the year-long
> independent work I did to reach this literary thread and this novel
> algorithm.
>
>
>
You can show it at due time: conference and when you give a talk. But please say explicitly "I had this idea and my co-author did have to sit through weekly meetings with me mostly failing to articulate mathematical ideas orally".
It will be then clear who had the idea and who formalized it (please note: I am being a bit tongue-in-cheek).
>
> If this paper is ever cited, it will be cited as Mew & Him
> (2023), and to be honest, it breaks my heart just seeing it that way.
> It is my brainchild. I rarely see a paper cited for its numerical
> experiments rather than the theoretical idea presented by it, and
> hence I lament that such a citation only seems to give me half the
> credit.
>
>
>
Without the numerical experiment, your paper will be perceived like "yes, crazy idea, how did this **unknown crank** published it on a peer-reviewed journal without presenting serious testing, let's wait for someone to perform proper tests on it" which means no one will test it, no one will prove it, no one will cite it, maybe 2-3 years down the line some master thesis will prove it and publish and cite your precious idea.
With the numerical experiment it will be perceived like "yes, crazy good idea, this **unknown person** published it on a peer-reviewed journal with a good set tests, relevant, I may build on it with citation". The work can then enter in the flow of citations of your field.
The numerical large testing experiment is then necessary. Would you have done without your advisor? no. Therefore it was *their* idea to perform them and they deserve recognition for that, so a co-authorship seems to me relevant.
Having an idea is a necessary, but not sufficient, requirement to publish a paper.
Upvotes: 3 <issue_comment>username_3: I also did research in NLP for quite a number of years, and at least in NLP specifically, single author paper is rare, and, to cater your worry, in a two-author paper people *never* think "oh, the first author must be freeloading off the more capable second author".
In NLP, so far I've seen only long-term professors who have published as solo author. It's completely normal and extremely common to have two-author paper in NLP. And when that paper is good, so far I've seen that the NLP community is giving credits to the first author.
tl;dr It's fine to publish a two-author paper in NLP, first author still gets the recognition.
Upvotes: 2 <issue_comment>username_4: If you want a career in academia, I think you are making a serious mistake by focusing too much on a single paper, especially if you reject the contributions of a collaborator.
Long term, you are probably better off being generous than selfish about such things as they can lead to the next paper and the one after that and additional people to share ideas with, extending your field and boosting your career.
How often does a paper come along that a career is "made" based on a single paper by a single author? Even Einstein had a lot of collaborators and a difficult time starting his career. It is easy to look back on AE and forget how difficult it was for him.
Also, note that "ideas" aren't enough. It is in the verification of those ideas that value is assigned. Often said that "ideas are free", though some would disagree.
Upvotes: 3
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2023/08/30
| 869
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<issue_start>username_0: Ahmedabad University is going to organize an annual [economic conference](https://ahduni.edu.in/academics/schools-centres/amrut-mody-school-of-management/events/5th-annual-economics-conference/). I have completed my graduation this year. A few conferences which were held at my university published the accepted papers in a booklet (made specially for the conference held). So I was under the impression that if I get my paper accepted at this conference, I might get published which would help me in getting admission to good graduate schools. But when I contacted the Ahmedabad University regarding the publication of papers, this was their reply:
>
> We do not publish papers in any conference proceedings. However, there is a best paper award.
>
>
>
Suppose that my paper doesn't win the best paper award, my question is: if they won't publish my paper in any of their proceedings or booklets, how would I be able mention it in my CV and how would the recruiting team of my target graduate schools be able to access it to evaluate the level of my work?
How would a recruiter of a Graduate School regard the student who had submitted a paper in such a conference, but didn't win the best paper award?<issue_comment>username_1: Even if conferences do not publish proceedings, the conference program is normally published on their website and can be accessed even after the conference is finished. So you have proof that you actually gave a talk at the conference.
If you want recruiters to be able to access your presentation, you can always upload it to an online repository afterwards (check copyright policies of the conference) and add the link to that in your CV.
Upvotes: 1 <issue_comment>username_2: I have never been to a conference in my field (Biology) that publishes conference proceedings. All you get is a booklet with the conference program, which lists the presentations, sometimes with an abstract. This is what you use as evidence that you presented, for your CV, reimbursement (if any) from your own institution, etc.
As @username_1 says in their answer, most conferences will post their programs online. That the particular conference you want to attend does not have its act together is concerning. But still, you should get a conference program which can then photocopy and use as evidence.
Upvotes: 0 <issue_comment>username_3: Literally, it doesn't hurt and may help. Listing it might lead to productive conversations during the application process. Be prepared.
For such things that leave little public record you can point to in a CV, I suggest you talk with those professors who are writing letters of recommendation for you and, supposing they know about the work and the conference, mention it in their letters.
It is one thing for you to say something unverifiable about yourself in an application or a CV, and quite another if a respected academic says those same things.
And, in any case, you should use letter writers with whom you have a good enough relationship that such a conversation is possible.
However, you should list it as you would if there were a proceedings published. Name, date, location, etc. And name the sponsor if it is a professional organization.
Let me add, also, if you are really asking whether you should bother doing this in the first place, that yes, it is worth it. Conferences give the opportunity to network with people in your field and to give yourself and your work visibility. Don't be a "wall flower" at conferences. Use "coffee time" and such to meet people and talk about ideas - give and take. Over time you want to build a circle of collaboration. Conferences are a good place to do that.
Upvotes: 1 [selected_answer]
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2023/08/30
| 810
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<issue_start>username_0: In a few weeks time I will be having my viva exam and I was wondering of a few things regarding the presentation in which I will be presenting four algorithms from four of my published papers.
Since my advisor recommended that the presentation be less than 25 slides due to the viva time limit and given that each of the papers that is included in it is around 10-15 pages long I was wondering of how synoptic each of my algorithm presentations must be in order to meet the slide-number requirement.
I have already prepared the slides but I feel that the algorithm presentations are too brief to be very useful for presenting them. Since I haven't done such presentation for a long time I was wondering if you have any advise or tips regarding brief viva presentations.<issue_comment>username_1: Assuming that the "judges" will have an opportunity to question you after the presentation, your "detail" can be much reduced.
Prioritize your presentation and the number of slides devoted to each point by the overall "importance" of a concept/algorithm is to your overall work. Each big idea should have at least two slides: background/concept and results. The more important ones, or the ones that give the most insight deserve more detail. But don't try to replicate the papers in the presentation, trying to answer all objections/questions.
In the slides you can point to important details in the papers by page and line number rather than presenting all the details.
Don't interpret this as a suggestion to leave out all details. But focus time and space on the most important things and expect that questioners will fill in what they don't find clear. I suggest you have additional slides ready that you don't present initially but that you can bring up when/if questions arise.
I suggest that you run your presentation by your advisor prior to the actual viva if possible and permitted.
Upvotes: 0 <issue_comment>username_2: I recommend you *urgently* go back to your advisor to clarify both the audience and the time line of your viva. 45 min for a viva sounds way too short and this makes me wonder if there is a second component to the viva.
You should also find someone who recently graduated from your institution and ask them about their viva experience, as details can be very institution specific and generic advice from the internet might not help.
Having said this, in a viva in the UK, the examiners will have read your thesis beforehand, so they will know what you are talking about and you should pitch your talk accordingly. Typically what examiners are interested in is a) what exactly your contributions to the presented results were (ideally this would be clear from the thesis, but it can be surprisingly difficult to discern, especially as yours sounds like a "stapler thesis" consisting on published papers) and b) what you consider your greatest achievement of your thesis, i.e. how did your thesis contribute to progress in the field. That was the very first question I got in my own viva in physics, and as far as I can tell it's an absolute standard question for PhD exams, STEM or not.
So it's important not to get bogged down in the details (e.g. rather than explaining how your algorithm works, focus on what makes it special), but focus on the big picture. The examiners will typically bring notes and ask questions about issues they didn't understand in your thesis and also often about ones they did, just to ensure that *you* actually understand what you are talking about - it is an exam after all.
Good luck!
Upvotes: 2 [selected_answer]
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<issue_start>username_0: My brother has written a paper which is essentially a survey of different techniques to accomplish a certain security related goal. He has also managed to present it in some conference.
Unfortunately, I do not think that this paper meets the standard of a rigorous research article for a few reasons. For instance, the surveying done in the paper seems to be shallow. Essentially anyone who has done a first course in security, or seen a few textbooks could write such an article with some rehashing. I also think that the classification he suggests in the paper is not very coherent.
So, I believe that this paper neither meets the standard of a research paper (because it lacks novelty) nor meets the standards of a rigorous survey (since he summarizes secondary sources, rather than primary sources). I believe it would me more worthwhile to publish this as a blogpost, or in a newspaper column instead of as an academic paper.
I am not certain how reputable this conference is. I suppose there was an accept/reject phase, but there was no feedback from the reviewers (if there were any).
Should I have a conversation with my brother about this?
* Arguments for: This will inform my brother of what research articles typically consist of. Also, it is in the general interest of academia to not have tertiary material labelled as "research articles".
* Arguments against: This might offend my brother. Also, it is better for the academic system to collectively express their assesment via standard channels (reviewer feedback, citations, etc) rather than me expressing my individual informal opinion.
---
Edited to add more context:
* My brother is a second year undergraduate student.
* This paper is co-authored with a professor in his university. However, (based on their Google Scholar profile) it does not seem like they have a solid track record of publishing security related papers. Most of their papers seem to be unrelated to security, and some of their most cited papers seem to be related to management/leadership.
* While this institution happens to be reputed, it is not reputed for their research (as far as I know). I am led to believe that this is the standard to which publications are held in this institution (and also by this certain professor).
* I am a graduate student, several years into my program.<issue_comment>username_1: Sure, tell him if you don't think the article is publishable. It's a bit hard to tell by your description if this is really not publication worthy but I'll take your word for it.
I guess the bigger issue is why does this matter? Is your brother in academia? At what stage of his career is he? At what stage of your career are you?
Constructive criticism and useful feedback is different than just dumping on his work, you probably can't go wrong with the former.
Upvotes: 2 <issue_comment>username_2: Whether you have an obligation or not is probably dependent on cultural norms, including those of your family. In general, though, you wouldn't have an "obligation" (I *must* do this), but likely it would be doing a service to him to learn the standards.
So, whether there is an obligation or not, I suggest you give it a try, gently, perhaps, if you worry about his reaction. And make it clear you aren't the judge.
This would be especially valuable to him if additional effort could bring it up to standard. Having a first attempt at a publication rejected is pretty common, though, and an education in its own right.
You might ask him whether he would value your opinion on what you think the response of reviewers might be. You might also point him to papers in a reasonably close journal and point out what elements made them acceptable.
Upvotes: 2 <issue_comment>username_3: I would not call it an *obligation*. However, I would assume that telling a brother your opinion on their work and (potentially) giving them an advice is not an issue and a common everyday behavior. I don't see a downside. If he would be offended, he needs to be told twice as much.
Upvotes: 2 <issue_comment>username_4: #### Don't pollute your sibling relationship with critical academic feedback
There are plenty of people who can give your brother critical feedback on his research article, including journal referees and other academics. Not only are you under no obligation to be the one to give him critical feedback, but it seems to me that as his sibling you are poorly placed to do this. (Why not tell him that he's not very good looking while you're at it.) I recommend that you leave the critical appraisal of defects in his research to journal referees and other non-related parties. If you are in a position where you have academic expertise that could be useful, then presumably you also know other colleagues who could do the same as a favour to you, so that any adverse feedback comes from someone who is not his sibling. If you must involve yourself with his paper at all, you should consider doing so in a more positive spirit --- i.e., help him identify ways he could *improve* his paper to bring it up to a standard where it can be published.
Upvotes: 4 <issue_comment>username_5: Your brother seems to have written a review paper, and those can be important contributions to academic literature. I don't see a reason to share unsolicited criticism.
Upvotes: 1 <issue_comment>username_6: Has he asked you for your opinion on whether it's publishable? Is there something on the line, e.g. the professor won't pay for publication and he/your family would have to foot the bill for submission fees? It appears like you're trying to take on the role of mentor here instead of brother and it's unclear why you feel like you need to take on that role (as you say, he has a mentor, even if you don't feel there credentials are as strong as you might personally prefer, but perhaps they have contacts and expertise that aren't immediately obvious). Is this typical for your dynamic with each other? Is this something he usually responds to positively?
Rather than potentially creating an issue in your personal relationship, it seems like it could be the better path, if your brother has *requested* help to put your brother in touch with security researchers who might perform peer review outside of the publication process, e.g. your PI or postdocs you work with. This would allow you to maintain a supportive family member role while also getting him the advice you feel he needs from people you respect. It's also worth keeping in mind that it's not uncommon for work done in undergrad to be published in undergrad-specific journals with somewhat different standards and that if he's just a sophomore now, this may well not be the final draft. And besides, not everything has to be top tier work to be valuable or publishable.
Upvotes: 1 <issue_comment>username_7: Leave your brother to submit the paper and you will be surprised that others will give positive feedback and might even see that the work is worthwhile for publication. In any case, it is your brother who clearly knows the question he is answering. You might also be having a 'I know the person' syndrome where we label people as competent or not competent to accomplish a task depending on our interactions with them.
Thank you
Upvotes: 1
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<issue_start>username_0: I have obtained multiple bachelor's degrees and a master's degree. I'm very motivated to pursue an academic career, for which obtaining a PhD seems like a necessity. However, I find it hard to decide on what kind of PhD positions I should be applying to. I often feel like a subject would be interesting enough to work on for multiple years and fits my master's degree quite well, but I really want to be moving in a different direction (specifically, I have two bachelor's, in mathematics and in computer science, and a master's in AI; after my master's I sadly have to conclude that I prefer topics on the border of computer science and mathematics rather than most of what's considered AI nowadays).
I'm having very little success in pursuing those PhD positions that look the most interesting to me. I feel like I would have an easier time if I broadened my search to include any subject I think I could keep up for 4 years, but I worry that this would 'lock me in' to this area of research.
Are my feelings justified given the way things work in academia and would it be justified to say that wanting to pursue an academic career I should not be applying to anything that straightforwardly doesn't fit that career path? Should I be happy to get into any PhD program at all, and accept that my options are rather limited? Or am I worrying needlessly, and would it not be at all unrealistic to make major lateral moves within my academic career, towards mathematics?<issue_comment>username_1: A metaphor: The dinosaurs were highly specialized and the "fit" for their world was superb. Hence, they grew very large and even more specialized. Then, one day, the world dramatically changed and ...
If you choose today, to specialize for the hottest possible topic today, knowing that your career will only begin in several years, say about seven, then you may find that the world has dramatically changed in the interim. People may be looking in other directions, but also, in the interim period, many (many) other people have joined that hot topic and you may find the zone completely flooded. "We'd love to hire you but we don't expect any openings for several years. Sorry."
This happened to me, actually, and I found a very difficult entry into academia, even in mathematics as a whole, because of economic conditions that changed academia and the possibility of hiring new faculty at any level. The world changed over the course of about two years from a hot hot zone to an empty wasteland (In my case, it was the loss of science funding after the US landed on the moon - a loss no one predicted.)
At some point you will need to specialize to get a doctorate, but I suggest that you don't do that too early, or, at least, that you keep open a lot of options. And, stay open to other options as they arise. And, all the better if the skills you get, even while specializing, are applicable in a wider domain.
At the moment, the STEM fields are better bets than the humanities. Both Math and CS are good choices. That can be expected (predicted) to continue. But, AI may be in a passing phase for its "heat index". Only a very small part of AI as a whole is in the news now. That might pass. The important problems there might get solved in the next few years with lots of people looking at them. Or not. It might open more. It might close. The issues with such things as ChatGPT could, perhaps, renew interest in the humanities. For myself, I'm not looking forward to the day when news is generated by amoral, brain-dead robots, whether you call them intelligent or not.
I find it wiser, for most people, to choose a path that they will enjoy following even if it doesn't necessarily lead to fame and riches at the end. If you love math, then do math, though it may lead you to a job that isn't what it might have been "if only...". But the person I describe here may not be you. Good luck then. I hope you make it.
If you try to make choices that lead to a situation that is all (Full Professor at Harvard or MIT) or nothing, then you might get lucky (and it will take luck beyond your control) or end with nothing. Many people can build a fulfilling life teaching math or CS at a liberal arts college, and it is more likely that there will continue to be demand for that than for specific sorts of high-octane research in a narrow field.
Prediction is hard. Especially about the future.
Upvotes: 3 <issue_comment>username_2: Ideally, I would tell you to follow your passion.
Instead, I suggest that you follow your passion while also looking at what you might do when you are done.
More realistically, I would submit applications to applied fields that interest me.
I give this advice for two reasons.
First, academic jobs are hard to get.
This will give you a good backup career outside of academia.
Second, there is less competition because people have other career options outside of academia.
Thus, all the graduates from your program will not be competing for a limited number of positions.
For example, pick engineering over (pure) physics; statistics/data science/applied mathematics over pure math; fisheries science over biology; or clinical psychology over academic psychology.
Look at where the alumni from the programs you are looking at end up.
They are the best predictors of your options when you graduate from a program.
Upvotes: 3 <issue_comment>username_3: Be very selective about your choice of *advisor*, as much as you can, and then about your choice of field.
I say this because you sound like you are more interested in chasing the research frontier, rather than settling down with a stable technique and deciding how to apply it. At the frontier entire fields emerge and evaporate on the timescale of a PhD. The field you go for when you graduate might not even exist when you enrol, making it impossible for you to study a PhD in it!
That's why you should optimise for your advisor. Their friendship and guidance will be the highlight (or lowlight) of your PhD. A good advisor will mentor you in productivity, wellbeing, networking, multitasking, working with students and admin, finding jobs and grants, and putting your distinctive touch on your research style. They can open doors for you and give you objective feedback. And if you find yourself in a good and healthy research group, you will immediately have a network of future collaborators to give you a leg up.
*That's* pivotal in choosing where to do your PhD, and you should work as hard as you can to find a good advisor. If it means picking a field you're a little less excited about, so be it.
Upvotes: 4 <issue_comment>username_4: You are making a good point and you are asking the right questions. However, instead of answering them for you, I'd rather provide some insight based on my personal experience that I think are in line with your concerns because, after all, you are facing a very important decision and in the end, you will have to make a decision yourself for which you will be the one who will face the (hopefully pleasant) consequences.
Knowing that you have already made your mind to pursue a career in academia, I can assume that you already know that research can be hard and also, I assume that you are already familiar with all the things that could be or are wrong/unpleasant in/with academia. To name a few, I could point out to the publish or perish atmosphere, the limited number of opportunities, high-level of competition and etc. So, in order to make your decision, I would recommend to keep these factors in mind as well. Because, starting a PhD is going to be just the beginning of the journey, and for most part of the journey, you will be on your own. Therefore, because of this, I'd suggest to keep the following two points in mind too, among others:
1. Select a field/subject that you truly enjoy thinking about and working on. As I said, doing research, both during and after finishing your PhD, is going to be hard. There will be so many long hours of feeling lost, getting bad results, frustrations and making little, if any, progress. And to make things worse, for the majority of times, there will be little help from anyone else. This is mostly because, doing research means working on a problem that has not been solved before. So naturally, there are not many people who even may have heard about it. Even if you are lucky to be with a very supportive supervisor, the chances are that they will not be of great help when it comes to solving the problem except providing moral support and pointing you to some of their previous research that may be of relevance to your work. Therefore, research can be hard as it is even if you love your topic but it will become easily unbearable if you do not.
2. Select a field/subject that you know you can be prolific at. This point comes after the previous one but nevertheless, it is very important because, to be successful in the academia, you will need to be prolific. As I mentioned earlier, in the academia the opportunities are limited and it is still suffering from the publish or perish culture. Therefore, even if you enjoy your research a lot but do not produce results (the kind of results that academia deems acceptable), you will have a difficult time finding post-doc positions, securing a tenure-track position and receiving grants.
Upvotes: 0 <issue_comment>username_5: There already has been quite a bit of advice, but as an addendum to all of the other posts about the primary importance being your choice of advisor, I would say to consider what you plan on doing post-PhD. and make sure your decisions map onto something that will contribute towards that. Namely, I would consider:
1. Do you want to work in industry?
2. If you stay in academia, do you want to be more teaching-oriented or research-oriented (and from 100% in one direction and 100% in the other, what do you feel would be the best balance)?
3. If you stay in academia, would you want to work in a CS department or a math department?
As others mentioned, some advisors will be better at some of these than the others. If you want to be research-focused and go to an R1, you should get a rockstar advisor with a track record of getting students into R1s. If you want to be more teaching-oriented, you should have an advisor who isn't clingy and lets you do some education research on the side (and select an institution that lets PhD students teach courses). And if you want to go to industry, you should get an advisor who will be happy to let you go to industry internships each summer (and ideally a track record of students going on to industry).
However, all else being equal (ie: having two advisors who both are good for your goals without anything strong pushing you towards one or the other), I would in general suggest going for the CS degree. In general, CS is "easier" to move into industry, and also easier to get an academic job (whether it is at an R1, a PUI, or any other type of institution).
However, it is generally rare for CS degrees to be in a math department, while the other direction isn't that uncommon. So if for whatever reason you are set out on being in a math department, then the tiebreaker might go to the math option. But otherwise, the tiebreaker should be towards CS.
Upvotes: 0
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<issue_start>username_0: For instance, say I introduce the term "macular degeneration" in the abstract and follow it with (MD) to establish the abbreviation. Should I just use (MD) from then on, including in the introduction? Or is the abstract often read separately and the reader expects all groundwork to be laid from scratch in the introduction, including re-establishing what the MD abbreviation means? Alternatively, I suppose you can avoid all abbreviations in the abstract and establish them for the first time in the introduction. Which is most standard/correct?<issue_comment>username_1: I would just reintroduce it. What's the harm?
Journals typically have a style guide for how they handle abbreviations, so ultimately you can follow whatever their guide is.
[APA also recommends redefinition](https://apastyle.apa.org/style-grammar-guidelines/abbreviations/definition):
>
> If an abbreviation has appeared in the abstract as well as the text, define it on first use in both places.
>
>
>
Upvotes: 5 [selected_answer]<issue_comment>username_2: Some folks will read only the abstract, others will dive into the paper, and yet others will read both. It’s a matter of taste in the end. I’d say lean to the side of the reader’s convenience as you see it at this point of your career. Your style will change over time.
Upvotes: 2
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<issue_start>username_0: While writing my PhD I've come across some writings that were OUTSTANDINGLY well written, handy and helpful.
Obviously I cited them, but as I understand, thesis citations aren't counted by various bibliometry tools. Also, in my opinion, a single citation doesn't show how much I enjoyed a paper.
Can I just send fanmail to the authors of such papers? I know that academics rarely get appreciation that they deserve. I doubt that we have prospects for any real collaboration, so I don't have any immediate interest in sending such fanmail. But maybe I can write it in a way that will be more beneficial than just pleasing someone?
To sum up:
* Is sending fanmail to a respected author a good idea?
* How to send fanmail in order to make it at least somewhat useful to anyone?<issue_comment>username_1: My first reaction is that it makes you seem like a sycophant (A person who attempts to gain advantage by flattering influential people or behaving in a servile manner: Webster). Especially since you mention "useful" and beneficial. This isn't Twitter (or its successor).
I can't envision an academic bragging about how many "likes" they got on their recent scholarly paper. Maybe for a laugh.
If you meet someone at a conference, though, you could say that you've gained a lot from their work. But email is just noise when it doesn't have things of substance. I'd recommend against it.
Upvotes: 2 <issue_comment>username_2: Yes! Send fanmail! :)
The professional academic math milieu does seem a bit "cold"... yes. True, there's no requirement of warm-and-fuzziness to be a math prof, but I myself do think that we toooo often forget/fail to tell people when we think their work/writing is amazing. I still do recall the few occasions when someone told me that some talk I gave was "stunning"... Sure, maybe I don't uniformly achieve that standard. :)
I do occasionally send email to people, some of whom I know, but by no means all, thanking them for writing something, and saying how much I enjoyed it. In some cases, people did respond, not only politely thanking me, but also saying that they had no idea what the reception of the paper/book was, since they'd heard back nothing at all. The feeling of "talking into the void"?!? That's a sad state.
I do also greatly enjoy *getting* a bit of fanmail now and then, confirming that all the stuff I put on-line is actually helpful/fun. :)
Upvotes: 4 <issue_comment>username_3: TL;DR: Everybody likes it if one appreciates their work. As long as you write honestly, informatively, and without further agenda, this is welcome and helpful. Don't worry about making it useful beyond the personal appreciation.
Scientists do their work because they like it and/or feel the need to do science - they do not (and should not) expect thanks beyond citations, invitations to talks, tenure, i.e. collecting the usual experience points of the academic dungeons and dragons game which can be turned into tangible uplevelling.
That being said, someone who expresses their real appreciation their work because it is particularly well done, or even just well written, is a welcome and unusual surprise.
If you write, don't be generic. Explain what in the paper was helpful, how, and why. State whether it was the writing of the paper, the organization of the material or whatever else that made it so useful to you.
The reason for that is that, not only does it show that you had a particular reason for praising the paper (rather than trying to ingratiate yourself), but it also helps the author understand what features of the paper were useful so that they can try and keep improving their future work (or keep doing it, at least) in that direction.
Additionally, note that they may have been criticized by a reviewer before for precisely those things that you liked about the paper (this happens more often than one would like; one reason why peer review is more often than not a lottery, especially in competitive venues); with only the reviewer's comment in mind they might be tempted in future not to write things this way - you would show them that there are readers that may actually profit from this style of presentation. While this does not resolve the authors' dilemma in what audience to write for, it gives them additional information to operate with in the future.
**What not to do**:
1. if your priority is to write about how much you enjoyed the paper, do this, but do not carry a secondary agenda beyond a friendly thanks/compliment/feedback to the author.
If you primarily want a collaboration, write a mail suggesting initiating a conversation or collaboration, only citing the paper as an inspiration for you to initiate this contact. That's fine. What's not recommended is to write effusively about the "great paper" only to insert some possibility of future collaboration. This looks weird and, to be honest, sycophantic [here I agree with username_1], if not creepily indirect.
Your mail should reflect what you want. Don't mix agendas.
2. Don't bother thinking about how to make the letter formally valuable. If you are not in an academically advanced position to write a reference to the author, you probably don't have the clout to do so, anyway - and that's not a bad thing, you'll have to do enough of these at some point, anyway. By feeding back that you enjoyed the paper, and why, you have done your part to help the author continue to do good work. And, in the end, that's what really counts.
3. [Thanks to <NAME> for this one:] do not expect a response. You may receive one, but should understand from the outset that your mail is likely to be a one-sided communication, at least on the immediate level. If you did your due diligence in highlighting what you liked about the work, you still have done your best in making the day nicer to the author of the paper and signalling what achievements you'd enjoy seeing repeated in the future.
Upvotes: 4 <issue_comment>username_4: The only addition I can provide is that I wouldn't have been accepted to my fully funded PhD programme if I hadn't reached out via some "fan mail".
Upvotes: 2 <issue_comment>username_5: Speaking as a nobody (a grad student, and not a very good one at that) who has gotten some "fanmail" in the past (one from a StackExchange user who was particularly grateful for a comment I left, one from a professor (who happens to also browse AcademiaSE fairly often...), some from friends), all of which I have saved away as treasures, I think that writing some kind words to someone to indicate that you *sincerely appreciate* some work of theirs (especially if you point out particular aspects that stand out to you!) would mean the world to them.
Perhaps for more senior and/or eminent members of the community, such fawning would truly be "noise", since it could be that they have already received enough of it in their life that they just don't want any more; but for more junior researchers who are just getting started, or even students, your "fanmail" may very well be the only positive affirmation they *ever* receive about something that "cost" them a great deal of blood sweat and tears.
As for anxiety about what is "acceptable" in a "fanmail", personally my views are along the lines of this following Tumblr comic.
[](https://i.stack.imgur.com/3c6wH.png)
Of course, the advice given in previous answers are good (write about specific things you enjoyed, etc.), but at the end of the day, sincere and kind words are sincere and kind words.
Also, I would advise you not to expect anything in return, though people are probably often polite enough to send a thank-you message in return. Some people may not know how to respond to praise, and/or have anxiety over responding awkwardly (especially in the situation of a more senior researcher writing "fanmail" to a more junior researcher), so try not take it personally if you don't get any reply, or the reply takes a long time. (There are of course infinitely many other reasons someone may not respond to a "fanmail"; in any case, try not to take it personally.)
Upvotes: 1 <issue_comment>username_6: Firstly, you have not said what the "writings" are.
I doubt if you read any particularly lucid published papers - clear research papers are not something that are usually submitted for publication owing to the space limits. Nor are they encouraged by those editors reviewing the papers. But if you have found some and they are in your own field of interest, praise the Lord, La Olam.
I think it far more likely that your much-appreciated writings would be in a text on the topic: the author has much more latitude spacewise and in regard to how they express things in a text - and most technical publishers' editors seldom interfere with a good draft.
Yes, getting a **brief, measured and calm** note of appreciation from a colleague is nice for those who have the gift or the determination to produce a well-written paper or text chapter. (Naturally text authors would also love to hear you say that you are recommending their work as reading material for an undergrad course you are giving . . .)
More useful would be an appreciation note with perhaps one or two suggestions. The latter need not be w.r.t. the writing but maybe on content, e.g. applications that the author may be unaware of or diagrams/photos/tables/schema that might get a concept across quicker to readers than via words.
One last thing is a certain "thought experiment" that many of us should conduct before we do something we haven't done before and we're not sure how the other party will receive it. Imagine your scenario of writing a note of appreciation for a well-written paper/book to a professor was a first scene in a TV movie . . . Now, how do you imagine the rest of the movie-story is going to pan out ?
If you find yourself moving away from mere academic communication things and into a whole new interpersonal sphere, maybe this isn't such a good idea.
Upvotes: 0
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<issue_start>username_0: My paper has been rejected (with a "Reject and Resubmit" status), and the Editor has recommended resubmitting it with the revision contents that incorporate the reviewer's feedback. I am considering not resubmitting it and submitting the article to another journal. Should I inform the editor that I won't be resubmitting my article to the journal?<issue_comment>username_1: **Not necessary to inform**
This is a line that the editor knowingly crossed when they sent 'reject and resubmit'. If they didn't want to increase the chance that you'll submit elsewhere, they would send 'revise'. (Functionally the two decisions are the same, but the first is more final in the sense that it increases the chances that the author never resubmits it.)
If you do resubmit it, then you should alert them that the manuscript is resubmitted (there'll almost surely be an option to do this in the editorial management system). If you don't, they'll forget about your manuscript.
Upvotes: 4 <issue_comment>username_2: >
> *Should I inform the editor that I won't be resubmitting my article to the journal?*
>
>
>
[Essentially, your paper has been rejected](https://academia.stackexchange.com/a/56534/162770) (Fomite, 2015). There is no obligation to formally withdraw or inform the Editor. However, there's also nothing stopping you from informing the Editor if you so wish.
I understand that '*reject and resubmit*' is not explicitly covered in the Academia [typical workflow of a journal](https://academia.stackexchange.com/questions/55665/what-does-the-typical-workflow-of-a-journal-look-like-how-should-i-interpret-a?noredirect=1&lq=1).
Depending on which lens on looks at it, *reject and resubmit* is synonymous with *revise and resubmit* or *major revision*. Yet, there're (*subtle*) differences between them. They also have different implications in terms of publication metrics.
Upvotes: 3
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<issue_start>username_0: I have a bachelor's degree in math (from Ghana) and for my final year project, I did something in applied topology; I explored the application of persistent homology to topological data analysis. I am considering applying for a master's degree and would like to do something that directly relates to my undergraduate project. From my research, any master's program that offers algebraic topology will best suit my preference. However, I have no intention of staying in academia. While I enjoy research, I would rather work in the industry, full-time, and then do mathematical research as a sort of pastime.
I am currently learning to be a professional data analyst. I am worried that with if I do my master's in a pure math field I will struggle to transition to industry. Any advice for me will be most appreciated.<issue_comment>username_1: A math degree is the last reason why anyone would struggle in the industry. While it may be country dependent, fields like data science/insurance/logistics etc. are full of people with math degrees and some positions even require one. I would argue that math is the best degree to have for those jobs, since understanding and using the *correct math* is the difficult part of the job. Using the *IT tools* (R, python, Excel, sql etc.) is the much much easier part.
Upvotes: 3 <issue_comment>username_2: In pure math, I'd guess that the job opportunities exist, but are very rare. Only a few companies can afford (in their thinking) to support pure research as it has no guaranteed payoff. Research in industry is mostly product focused, even at places like IBM, which does, by the way employ a number of "pure" researchers. But if it is hard to justify how you contribute to the "bottom line" it is hard to find a place.
Google, Oracle, IBM, and some others have a small (by the standards of the company) pure research staff, but most other companies don't, and rely on universities and government to make the fundamental breakthroughs that they ultimately depend upon. One major difficulty with pure research is that it is difficult to set time constraints. Insight and problem solution in math (and some other fields) doesn't and can't happen on a schedule. It happens when it happens if it happens at all. It is a risk, then, that a few companies are willing to take, but only in a limited way.
But if you want to do pure math as a hobby, sure, you can do that provided that financing your lifestyle doesn't take so much out of you that you have nothing left in you at the end of a long day.
If you want to do pure research and get paid for it, then I suggest that you keep open the possibility that it might be in academia. Even in a liberal arts (teaching) college you have more opportunity for pure math research than you would spending your days in a cubicle at a company in, for example, the auto industry. Just be realistic about what industry really cares about.
I think this is especially true for math and probably physics. In chemistry or biology it is probably a bit different, since, for example, the pharmaceutical industry "product" research can be pretty similar to pure research in those fields. Math, not so much.
---
Applied math, on the other hand, has many more opportunities, including in finance, insurance, and others. But, applied math is very different from pure math, with different techniques and goals. The same would be true for other applied fields - applied physics, for example.
Upvotes: 4 <issue_comment>username_3: A pure mathematics program will teach you two sets of skills, one of which will be highly applicable in any career you choose, the other of which may or may not be.
1. First and foremost, a pure mathematics program will teach you general cognitive skills with respect to rigorous thinking, problem solving, and how to deal with impossibly complex tasks by tackling tractable pieces.
2. Second, the specifics of the work that you engage in will teach you particular skills that may or may not be applicable anywhere else. For example:
* Abstruse mathematical theorems and specific proof techniques will likely not be useful.
* Learning how to search through research literature to find useful theorems and proof techniques is more likely be useful.
* Even some pure mathematics may include computational exploration and data analysis, which is definitely useful.
Somebody hiring in industry will likely be interested in both what you can do right now and what your potential for growth looks like.
* If you are learning and producing visible evidence of competence with data analysis somewhere (whether in your program or outside of it), that will give you skills for "right now".
* The cognitive skills from your research program will more address potential for growth, if you can demonstrate flexibility of mind in how you apply them outside of the narrow context in which you've learned them.
Bottom line: there are valuable skills for industry available in a pure mathematics program, if you are flexible enough to understand how to apply them across disciplines.
Upvotes: 3 <issue_comment>username_4: I second everything username_2 said, but my undergrad was in pure math and I started on a masters program in pure math before ultimately transferring to law school so I may be able to offer some relevant experience.
As username_2 said, finding industry jobs that are truly in pure math is very difficult. I never succeeded. But finding industry jobs that appreciate someone with a background in mathematics, even if it is pure mathematics, is quite easy. I held jobs in programming, database administration, and data analysis in more than one separate industry.
Also while my current firm certainly cares more about my J.D. than my work in mathematics, the skill of thinking rigorously is always useful and I even make use of basic mathematical concepts surprisingly often in my work as a lawyer.
To somewhat add to what username_2 said, I can say that trying to do mathematical research as a hobby while having a full time job is challenging to put it mildly. While I still enjoy mathematics, the closest thing I have managed to do to research since I transferred out of the master's program is that I can still help my son with his math homework even though he's in college to be an electrical engineer. (I did manage to publish a couple of articles about relational algebra, but those were in trade magazines for database administrators about applying relational algebra to practical database administration and did not really develop a new idea so much as summarize old ones with practical examples). Perhaps you are more skilled or more disciplined than I am. Fermat quite famously did significant research as a hobby while being a judge. I have not managed to live up to Fermat's example.
Upvotes: 3 <issue_comment>username_5: The other answers provide decent general advice. But I fear that they lack the urgency that comes from having actually done this recently. For some background, I was just hired in the past 8 months as an assistant professor at a research university for a data science position, was also preparing applications for industry data science positions, and specialize in topological data analysis (TDA).
Say you want to be employable for data science positions (careful: "data analyst" tends to refer a different job) and get an industry job in a reasonable time frame at the end of a masters. You can do this in a theory-heavy course. If you are unfocused, it will cost you time (and salary) brushing up on skills during a job search after you graduate.
**What masters courses should you look for?**
It is absolutely essential that you find a course that helps you further develop a set of computer skills in addition to theoretical ones that will be visible to potential employers. An anecdote: I took an MSc like this, the courses included a full proof-based run through of Hatcher's algebraic topology. But also multiple courses on modern machine learning with significant coding components.
What won't help you get a job that quickly: Taking a course with no computational lectures, writing a very theoretical thesis without further developing your computational skills, and then throwing in your industry applications against computer science majors who won't cost an employer 6 months of time just to become productive. This isn't hypothetical: I've had multiple friends get done with very theoretical math PhD's, including specializing in algebraic topology, then take 6mo - 1 year of re-skilling and searching to get an industry job.
**What skills are your target employers looking for?**
I'd encourage you: Go look up job postings for data science positions you think you could be interested in, and look at the list of skills they'd like. They're going to include Python/R, SQL, probably familiarity with neural networks or CNN's, regrettably an increasing interest in Large Language Models, basic statistics, data cleaning, data visualization, etc. Some type of more serious memory management language like C++ couldn't hurt. Data science positions are also often interested in whether you have skills working with different *types* of data: Images, text/web scraping, "unstructured", geospatial.
You don't need to be an expert in all of them. Also, some demand for certain skills will change over time. You can't just blow building these up because they're all "easy", however.
**What about more TDA?**
If you take a Masters, TDA projects can be decent vehicles for a thesis that has some serious math while also benefiting from computer skills you want to build up to be competitive for industry position.
Computational topology and computational geometry for data analysis are not, however, particularly in-demand skills outside of academia. For example, persistent homology remains too expensive right now compared to much faster methods that are "good enough" for most use cases businesses currently care about. Obviously there's continual research work going into improving that situation, as the field is relatively young.
Which is to say, if you want to do more TDA/PH related work in a masters, but are angling for industry positions: It's something you can do, but you need to combine it with bulking up other skills.
Upvotes: 4 [selected_answer]<issue_comment>username_6: Effectiveness in industry jobs requires some software engineering experience. Math majors without significant demonstrated software development under their belt require a lot of on-the-job training by a peer, and that's assuming that the position even has such a peer available. Employers will not consider such an applicant if someone comparable but with developer skills is available.
If you didn't have code in several small projects reviewed by a professional, you'll face many hardships IMHO. I have dealt with numerical code written by grad students in math fields - and one thing novices have a lot of trouble with is tendency to copy-paste and inability to factor out concepts at different levels of abstraction. They even have trouble just figuring out what those levels of abstraction might be to start with - a fact perhaps puzzling given their math background.
I've seen plenty of numerical code written for Ph.D. dissertations by people without guidance/review by a software engineer that was an impenetrable mess that could be shortened to 1/4 the length while making it self-documenting, easy to understand in terms of the application rather than implementation details, amenable to unit testing, and so on.
If you can contribute to open-source math libraries/projects that have code reviews in place for contributors - that might be a good way to gain experience. I have no idea how much of it does with topology, though. Open source data analysis is all the rage though so it shouldn't be hard to find something where you could gain experience.
It helps already if you can "code your way out of a box" for simple repetitive data wrangling tasks - say scripting with Python, numPy and other relevant libraries. Even that is a leg up over some applicants. The ability to write maintainable code takes a long time to develop, so you won't be an expert in a year or two anyway. But at least some familiarity with industrial software development processes - a familiarity that can be built contributing to open source - will go a long way towards making you a more desirable candidate.
Upvotes: 2
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2023/08/31
| 1,067
| 4,561
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<issue_start>username_0: I wrote my master thesis in Germany and submitted it on time. After checking I notice some small typing errors and some problems with my references (minor ones, not a problem really). I just saw that I accidentally added the same paragraph (300 words) twice in a row. This resulted from how I prefer to use secondary programs to check my thesis for mistakes.
I wrote to my supervisor but he did not reply. I know it is not considered self plagiarism because it is my work, and I am not trying to get credit twice. I fear that I will fail because a master's thesis is not supposed to have errors such as this. Is there anything I can do? In German universities, corrections after submission are not allowed, so I can not delete this chapter.<issue_comment>username_1: I realize that German universities are pretty strict and I'm not there, but, in reality, the cause of the duplication may be the same as the cause of two two words being identical. (See what I did there??)
It seems to be a paste operation repeated with shaky fingers.
I would chuckle over it (in the US), but it isn't a reason to fail a person after years of work. That would be foolish. If they expect absolute perfection in document preparation then they would all be failures themselves.
For the record it is well known that proofing your own work is notoriously difficult. Your brain "knows" what is there before you start reading and "sees" what it expects to see.
I would relax. If it becomes a problem, which I doubt will happen, then deal with it then, perhaps through higher authority.
Make any corrections prior to publication, of course.
Upvotes: 5 <issue_comment>username_2: "Horrible mistakes" in research are usually ones related to methodology or interpretation and result in the conclusions having some fundamental flaw.
You're describing a typographical error. This isn't much different than misspelling some words, or having a few sentences that aren't quite grammatical. So long as your writing can be clearly understood, it is rare that anyone will care about limited typesetting issues. It would be absolutely absurd to fail a thesis for such a reason. Fix it if you can, forget about it if you can't.
Upvotes: 6 <issue_comment>username_3: I predict that a significant fraction of your audience will not even notice the error. They will assume that they simply nodded off while reading it.
Upvotes: 0 <issue_comment>username_4: It depends on how exactly the process works, but this sounds like "Accept with minor corrections" territory (assuming nothing else is wrong).
While I don't know the detailed process in Germany, when I submitted my MSc. thesis in Ireland (all those years ago...), MS Word managed to completely mangle about half a page of the text in the version submitted for examination, such that it was garbage. I completely missed this prior to submission. It turned out the external examiner either missed it or didn't care. The internal examiner flagged it up as a "minor correction".
My understanding is that it is quite common in the Sciences for thesis to get a long list of minor corrections requested from the examiners. Correcting an accidental double-paste sits right in the category of "minor corrections" as I understand it. If everything else is good, I personally, based on my experience, would expect it to be dealt with like that.
Upvotes: 2 <issue_comment>username_5: This mistake doesn't look horrible to me at all. It would be horrible if your reviewers see at horrible. Yours is marginally worse than a typo. Since Master thesis writers are not expected to be hiring editors, I wouldn't even bother to mark this if I were a reviewer. Forget about this, it's not worth your worrying.
Upvotes: 2 <issue_comment>username_6: After submitting my Master's thesis (also at a German university, albeit back in 2006) I noticed I had accidentally cut away half of a paragraph (I was using LaTeX, in which the %-sign serves as a comment and was summarising some percentages...). Nobody noticed (or maybe they did, but in the end nobody cared.) I assume it depends a bit whether you're in STEM/MINT, where the written text doesn't matter that much as you usually have already achieved some results with your thesis work; or whether you're in the humanities, where the writing itself constitutes the work and thus might be weighted a bit more.
In general, I'd assume like the other answers that this is all no biggie. You mentioned your supervisor didn't reply -- that also kinda points in that direction.
Upvotes: 2
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2023/08/31
| 1,055
| 4,074
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<issue_start>username_0: I am an RA with an unorthodox path. During my PhD I had to move from a group to working alone with a different set of supervisors that didn't have much of a connection to my topic and after my PhD they couldn't help. I am now an RA but I mostly do teaching and no research. My teaching experience is good but I don't have that many publications. I tried to publish some things from my PhD but they are now a bit dated and I don't have any connections to get involved in other projects. I tried to network but it is very difficult. So far this year I wrote a couple of papers, I was in 2 conference programme committees, I got 2 small grants but it is still not enough.<issue_comment>username_1: Nobody knows, really, "how to" progress in academia. Trying to progress in academia means taking part in a lottery. Someone might read a paper of yours and notice you, or it might go unnoticed. Being at conferences is good. Being a research assistant who is exploited to do only teaching sounds bad.
Upvotes: -1 <issue_comment>username_2: Yes, it is very difficult to advance without a circle of connections, especially collaborators. And you are in a particularly difficult position, I think, and may be being exploited to some extent. If they would offer you a permanent position, even as teaching faculty then it would give you a base.
But the solution to the problem is to develop that circle, I think. I had a very difficult time getting started even with people willing to support me and the market for faculty in academia seems to be very difficult at present (as it was for me).
First, try to find a mentor where you are. Look around at faculty who might serve - people you respect. Talk to them about your need to find a better position that is more open to advancement. You need a base from which to work and you need people willing to help you find that base.
The department head/chair has an ethical obligation to help you get started, even if they don't recognize that. If you can talk to them, expressing your career needs, perhaps they can help with money for travel and conference fees.
You are doing the right thing being on conference committees. Use those people to start with building your circle. Talk to them about your needs. Get the more prominent ones to introduce you to people with similar interests.
One can expand their own circle by getting introduced to members of the circle of others.
If you are introverted, find ways to overcome that. It can be difficult and it takes practice but it can be done. I doubt many here would tag me as very introverted, but at one time I was held back by an extreme reluctance to make my needs known to those who had the power to help. I know people who are "on the spectrum" who are also known as brilliant public speakers. They have learned to play a role and not let their "natural" inclinations to hide in the background dominate their lives. If this is an issue with you, add a comment and I'll say a bit more.
Upvotes: 2 <issue_comment>username_3: >
> *... but I mostly do teaching and no research. My teaching experience is good but I don't have that many publications. ... I tried to network but it is very difficult. So far this year I wrote a couple of papers, I was in 2 conference programme committees, I got 2 small grants but it is still not enough.*
>
>
>
As an add-on, give thought to *reflexivity*. You can leverage on your subject knowledge and teaching experience to write and publish papers on your teaching delivery, innovations in your teaching style/approach and assessment.
Innovation can be processes, pedagogical approaches, technological innovation, sustainable assessments: [Boyd (2000)](https://doi.org/10.1080/713695728), [Boyd (2016)](https://doi.org/10.1080/02602938.2015.1018133), [Adesemowo (2017)](https://doi.org/10.1016/j.stueduc.2017.04.005).
Through collaboration and showcasing your scholarship of teaching, learning and assessment, you might build (lasting) network. Your network will also gravitates towards your '*topic*'.
Upvotes: 0
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2023/09/01
| 787
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<issue_start>username_0: As I understand you cannot publish your paper in two different journals, I was wondering if the same rule applies to chapters in books. My research (52 pages long) was summarized into 20 pages to fit into a chapter of a book and in another language (Portuguese). Now, I would like to publish the same paper (in its entirety) in a journal, rather than a chapter in a book. Is it possible?
Thank you.<issue_comment>username_1: I would say that going from journal article to textbook chapter is fairly normal - as long as you hold copyright and the publisher wants to include the chapter there shouldn't be a problem. The goal of a textbook is to present known information to its audience.
Going in the other direction presents some potential issues.
1. If the work has been published in any format (other than some common exceptions such as preprints or theses) a journal might not accept the submission.
2. If it has already been published, you may no longer hold copyright. A derivative work *might* run afoul of some license or copyright agreement.
3. If there is no substantial new info included in the paper, you might have a hard time finding a willing journal even if it's not technically against the publisher's rules and there are no copyright issues.
In your situation, I don't think you can just submit as if the textbook chapter didn't exist. But I don't see any reason not to try to get your work published. Basically, I think you need to coordinate with journals and your book publisher to ensure that there are not any roadblocks.
Upvotes: 0 <issue_comment>username_2: You are phrasing your question in a slightly confusing way. It seems that what you have is a 20 page text that has already appeared in a book, and a 52 page text that you would like to submit to a journal. Is that correct?
In that case, they are hardly "the same paper". Rather, what you seem to be asking is:
>
> Can I write two different papers (a brief summary for a book and also
> a much longer journal paper) based on the same body of research?
>
>
>
To which the answer is a resounding yes. Of course, the paper is only likely to be accepted if it adds something substantial on top of the 20 page summary paper.
Note that this has nothing to do with one publication being part of a book and the other being in a journal. Your question suggests that you believe that if you tried to publish in a journal the same paper that has already appeared in a book (which is *not* what you are doing), then somehow different rules would apply then when you tried to publish in a journal a paper that has already appeared in another journal, but this is not the case. The difference between a book chapter and a journal paper is not really relevant to the fact that journals will generally not republish texts that have already appeared elsewhere. (At least I am confident that this is how it works for journals that I am familiar with.)
Upvotes: 1 <issue_comment>username_3: Strange question, because a journal article would have to be shorter than a book chapter, it would not be the longer version (at least that's my experience with journals). But if the second publication is an extended version of the first, and particularly, if it is a translation into a different language (as you say) they may count as sufficiently distinct to publish both, in principle. Otherwise, rework the stuff to make it distinct.
Upvotes: 0
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2023/09/01
| 348
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<issue_start>username_0: I'm considering generating a DOI for my thesis, but I wondered if this would be a problem if I wanted to write a paper out of it.
Theoretically, the paper would not be exactly the same as my thesis, but it would be pretty similar.
I've found equivalent questions here, but none of the responses were actually conclusive.
Does it depend on the journal, or there is no problem whatsoever?<issue_comment>username_1: This is journal/field dependent but in general getting a DOI for your thesis (or posting it on a preprint server or university repository) should not prevent future publication. Many journals, at least in my field, specifically state that theses are *not* considered prior publication i.e., you can submit articles derived from thesis work.
You should check whatever journals you want to submit to first though, just to be safe.
Upvotes: 4 <issue_comment>username_2: If you say that the journal publication would be *somewhat* different, then it does not seem to be a problem anyway. And in any event, the publication would get a different doi, since it would be a different object. The doi identifies the "object", not the content.
Otherwise, I agree with serlsano's answer: it depends on the policy of the individual journal whether they would tolerate it that the text is simultaneously available elsewhere. Assigning it a doi would somehow enhance the online presence of the manuscript, but that's a minor factor. So, yes, please check with the journal.
Upvotes: 2
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2023/09/02
| 806
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<issue_start>username_0: Genuinely curious! From my perspective the postdocs have even less freedom than I do (I work in a national lab, where although I'm a PhD student my experience sadly is more like an employee). I know research fellowships are different, but seeing as most people go PhD -> Postdoc, this to me does not seem like a step forward.
They are assigned tasks by our boss, and they have to do them. I remember this postdoc, smart guy, who had an interesting idea but the boss said "sounds interesting but that's not your work" (something he has said to me). Now I can (and have) bent the rules to do more of my own thing. I don't have to come in 9-5 in the same way the postdocs do. So for less research and work freedom they are paid a bit more than me. But after tax, it's not some huge difference?
**So why don't we see more people do PhD --> PhD, instead of always PhD --> Postdoc? Seems like the life is better!**<issue_comment>username_1: Postdoc is a job title that covers a large number of positions and employment conditions.
Some postdocs have significant project flexibility, some are hired to work primarily on a specific project. My postdoc had zero constraints on what projects I pursued, for instance.
Largely speaking, postdoc positions pay substantially more than a PhD. The range I've seen in math is something like 2-3x annual salary increase. This is a very big difference, and taxes don't diminish it substantially.
Departments do not routinely hire PhD holders in nearby disciplines to pursue a second PhD, both because this would be seen as exploitive and because it's a waste of all parties' time.
To put it more shortly: I think you have Dunning-Krugered yourself on this subject. A postdoc is usually the only available job type in academia immediately after graduating with a PhD and pays more.
Upvotes: 4 <issue_comment>username_2: Many people consider having been formally employed and paid for their work a step forward compared to being a PhD student (who, depending on the country, may not be paid, or may themselves have to pay for the training/tuition). A formal employment allows one to pay taxes, make pension plan, become eligible for mortgage, etc. For researchers from abroad, postdoc employment allows them to get a work visa and years spend doing postdocs count towards their immigration track in the way which PhD career does not.
As for research independence, it's true that postdocs sometimes do not enjoy the degree of academic freedom they deserve. But the same can be said of PhD students, who, depending on their PI and lab customs, may feel micromanaged and overly directed.
Postdoc is a step towards independent (tenured) academic position, which is considered the point when one fully embarks on their own research journey.
Upvotes: 2 <issue_comment>username_3: Postdocs are paid 130% to 330% of what PhD students are paid. (This is usually less than what the postdoc could get for a non-academic job.)
Switching to a new university is considered a way to gain valuable experience.
The question and other answers discuss differences in working conditions; I would not generalize about working conditions. These can vary greatly depending on the individual job. Working conditions also vary greatly for undergraduate students and deans.
Upvotes: 2
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2016/08/02
| 801
| 3,205
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<issue_start>username_0: Besides being "one of the 7 meta-questions every site should ask", it's just plain important. An "AI Stackexchange" site has been tried before, at least once, and possibly a few times. And in the past, it's been killed for lack of activity.
So, how do we promote this site well enough to attract a critical mass of participants? And how do we get people to participate?<issue_comment>username_1: As Franck neatly put: First step would be to clearly define the scope of the site.
Next, there are very active Data Science, AI and ML communities on Reddit and other community sites like facebook groups, etc; and they would be an excellent way to get new users.
And as AI is a very hot topic right now, we would be getting traffic and users as long as we keep the scope well pruned and the posts well curated.
Upvotes: 3 <issue_comment>username_2: Once we figure out what we're about exactly, we need to haul in some real experts.
This is a good idea right here: [Can we send messages to young researchers who have recently published papers in artificial intelligence related journals during the private beta?](https://ai.meta.stackexchange.com/q/22/75) Scholarly papers generally include their authors' e-mail addresses. Papers that don't have e-mails will at least have author names, and some Googling could turn up contact information.
Upvotes: 2 <issue_comment>username_3: Here's one idea: Search Meetup.com for meetups which are related to artificial intelligence, and post this link to their message boards and / or mailing lists, with a brief note saying "you may find this of interest".
Upvotes: 2 <issue_comment>username_4: I think that we could try to promote the site with people from a broad range of disciplines. I remember seeing on Area51 what other people committed to, and there were mostly engineering or computer-related sites. Perhaps we need some philosophers, some psychologists, some neuroscientists and linguists here.
Maybe encouraging questions on other sites of the SX-network?
Or social networks posts?
---
I also wanted to add another site which has overlapping topics: [Cognitive Sciences](https://cogsci.stackexchange.com/)
Upvotes: 0 <issue_comment>username_5: I think Stack Exchange A.I. site is self-promoted and it does not need promotion. We just need a bit more time, that's all. I think this site has enough active experts so far, so our *answer ratio* is fine (1.8 at the time of writing).
Secondly given Stack Exchange higher ranked [SEO](https://en.wikipedia.org/wiki/Search_engine_optimization) abilities, people looking for A.I. answers will quickly find this place. Especially having in mind that A.I. is more likely to be the next big boom for this century, I believe next year we'll hit the [site healthy stats](https://ai.meta.stackexchange.com/q/1225/8) without even promoting it.
Although if we decide to promote it, we need to be careful, as promoting this site to the wrong communities, this can result in lot of people asking the broad and opinion based posts.
Artificial promotion isn't a good one, but sharing the AI links to the good answers on relevant forum posts or reddit-like sites is a great start.
Upvotes: 0
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2016/08/02
| 2,240
| 8,111
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<issue_start>username_0: Are all questions asked on stats and data science SE also on topic here? Or is there some rule such as (on-topic in stats or data science SE implies off-topic here)?
Data science and the stats SE already have a huge overlap (>~80%), I am worried to have a third SE that also significantly overlaps with them.
---
As a side note, many other SE have an AI tags, e.g.:
* <https://philosophy.stackexchange.com/questions/tagged/artificial-intelligence>
* <https://worldbuilding.stackexchange.com/questions/tagged/artificial-intelligence> (for the most sci-fi questions)
* <https://cstheory.stackexchange.com/questions/tagged/ai.artificial-intel>
* <https://cs.stackexchange.com/questions/tagged/artificial-intelligence>
* <https://cogsci.stackexchange.com/questions/tagged/artificial-intelligence>
* <https://hsm.stackexchange.com/questions/tagged/artificial-intelligence>
* <https://stackoverflow.com/questions/tagged/artificial-intelligence>
* <https://gamedev.stackexchange.com/questions/tagged/ai><issue_comment>username_1: No, data science and the implementation of artificial intelligence are off-topic. [A community manager explicitly said so in the Area 51 discussions for this site.](https://area51.meta.stackexchange.com/a/24016/136466) There have been at least two AI sites on SE before, and they've all failed. We need to bring something new to the table, especially in the private beta stage. Once that's over, we can consider whether we can bring a new viewpoint to such questions.
Upvotes: 4 <issue_comment>username_2: Definitely not. In some minutes we can see lots of questions asking for specific technical solutions about neural networks and genetic algorithms. I agree with Ben that we need to make this site different and start migrating all these questions to other sites, where there *is already* an answer to most of them.
Why would we want to ask them again?
(apart from rush for reputation)
Upvotes: 3 <issue_comment>username_3: I'm going to say "yes". That doesn't mean we need to *solicit* those kinds of questions, but if / when they show up, I think we should just handle them "organically" if you will. That is, up/down vote them, answer them, comment on them, etc., exactly as we would anything else. I don't see any point in us taking on the effort of cross-checking with other sites and migrating questions, etc. IF the SE infrastructure makes it super easy to do some in some cases, then sure, fine, I guess. But I oppose having ai.se mods waste their energy and time dealing with pedantic quibbling over which site is "most" appropriate for a question.
Upvotes: 2 <issue_comment>username_4: **Yes**
I am sorry to be the one who posts Yes, but as we are in the beta, I want to be straight forward.
In addition to that, AI is also on-topic in the CS site. [I was the one who raised this in the definition phase](https://area51.meta.stackexchange.com/q/22939/142759).
So, a lot of topic which this site aims to cover are already covered in the existing sites.
Upvotes: 3 <issue_comment>username_5: [@RobertCartaino suggested in this post](https://ai.meta.stackexchange.com/a/72/8) that:
>
> "programming" and "implementation problems" be explicitly listed as outside the scope of this site
>
>
>
in order to direct the authors to sites which were explicitly created to handle these "technical" issues.
This site failed already two times, because people didn't ask the right questions and most of them were already covered by somewhere else (e.g. Stack Overflow, Statistics, Data Science, and similar applied sites).
Basically:
>
> Data Science is an applied site for all the programmers/statisticians/mathematicians who are trying to make this stuff work.
>
>
> a more-comprehensive site which included the development of AI, machine learning, statistical tools, big data, NLP, data mining, etc,
>
>
>
so:
>
> No, machine learning as far as implementation goes is not on topic for this site.
>
>
>
and:
>
> if this site were to simply start reiterating the implementation/tools questions that are already covered elsewhere, this site will not likely make it out of private beta.
>
>
>
---
On the [other hand](https://area51.meta.stackexchange.com/questions/24014/will-machine-learning-be-considered-as-on-topic/24016#comment38287_24016):
>
> Everything in the proposal is considered when evaluating whether the site would likely be viable. If the proposal looks good across the board, that is the "compelling case"
>
>
>
Upvotes: 2 <issue_comment>username_5: I believe questions asked at [Stats.SE](https://stats.stackexchange.com/) about [artificial intelligence](https://stats.stackexchange.com/questions/tagged/artificial-intelligence) should be on-topic here as well, because:
* since past 6 years there were only [~73 questions asked about AI](https://stats.stackexchange.com/questions/tagged/artificial-intelligence), 1/3 of them still [unanswered](https://stats.stackexchange.com/questions/tagged/artificial-intelligence?sort=unanswered),
* 40% of question about [machine-learning](https://stats.stackexchange.com/questions/tagged/machine-learning) are also [unanswered](https://stats.stackexchange.com/questions/tagged/machine-learning?sort=unanswered), try scrolling.
You may suggest they may lacking of AI experts there, so lets move there. However not all AI experts are using or are interested in statistics models with AI.
For example I'm no where near as statistician, I've no idea about cross-validation aka rotation estimation models, but I may use and implement practical AI algorithms.
Therefore I think our site has already its own distinct and unique scope in comparison to Stats.SE, because it is about pure Artificial Intelligence and beyond.
You can still asks about AI at Stats.SE, but it should be focused to *statistical learning*. To support that, [check this post](https://stats.meta.stackexchange.com/a/2095/12989):
>
> Question on AI including a comparison with statistical learning would be pretty clearly on topic here.
>
>
>
They were accepting even without that, but I think most likely because people didn't have the right place to ask. If they've asked, didn't have much attention (maybe AI experts aren't interested in statistical models).
If you've question about theoretical AI, you can consider asking at: [CSTheory.SE](https://cstheory.stackexchange.com/questions/tagged/ai.artificial-intel) (not active either).
We can only hope that after [6 years](http://blog.stackoverflow.com/2010/12/no-artificial-intelligence-in-area-51/) of previous failures, we're able to break some ice this time.
We've one-time final opportunity to not have AI spread across the whole network:
Stats.SE, CSTheory.SE, CogSci.SE, Philosophy.SE, Worldbuilding.SE, SO.SE, CS.SE, HSM.SE, Robotics.SE, GameDev.SE, gosh where else, with no real AI experts in one place.
So basically the goal of this site is as pointed by [@lejlot](https://area51.meta.stackexchange.com/questions/11658/faked-artificial-intelligence-like-in-game-development#comment18885_11709):
>
> To bring people from this one particular field, which exists in
> between all above in one place. I see the reason behind it - as now
> questions regarding AI are scattered across these sites and get very
> little attention from actual experts, who also visit just a subset of
> these. Additionally - on each site these questions are tagged in a
> different way, so it is impossible to track them. Unification (new
> site) would make all of it much easier (and in fact - possible for the
> first time).
>
>
>
If this going to fail this time, people still will have to have 10-20 different accounts to ask the right questions on the right sites (which is very inconvenient). This would be very sad.
---
To summary, [some say](https://www.quora.com/I-once-heard-statistical-learning-is-not-the-path-to-AI-Artificial-Intelligence-what-are-the-arguments-that-support-this-statement-claim):
>
> statistical learning is not the path to AI (Artificial Intelligence)
>
>
>
but it's open to debate.
Upvotes: 2
|
2016/08/02
| 2,196
| 8,075
|
<issue_start>username_0: I've seen several questions that use the [artificial-intelligence](https://ai.stackexchange.com/questions/tagged/artificial-intelligence "show questions tagged 'artificial-intelligence'") tag, sometimes as the only tag on the question. That is not useful for categorizing questions, so please don't add this to your question.
For this reason, the site name is usually blacklisted as tag name.
* So the [bug](https://ai.stackexchange.com/questions/tagged/bug "show questions tagged 'bug'") is: Why isn't [artificial-intelligence](https://ai.stackexchange.com/questions/tagged/artificial-intelligence "show questions tagged 'artificial-intelligence'") blacklisted?
* The [feature-request](https://ai.stackexchange.com/questions/tagged/feature-request "show questions tagged 'feature-request'") is: Please blacklist [artificial-intelligence](https://ai.stackexchange.com/questions/tagged/artificial-intelligence "show questions tagged 'artificial-intelligence'").<issue_comment>username_1: No, data science and the implementation of artificial intelligence are off-topic. [A community manager explicitly said so in the Area 51 discussions for this site.](https://area51.meta.stackexchange.com/a/24016/136466) There have been at least two AI sites on SE before, and they've all failed. We need to bring something new to the table, especially in the private beta stage. Once that's over, we can consider whether we can bring a new viewpoint to such questions.
Upvotes: 4 <issue_comment>username_2: Definitely not. In some minutes we can see lots of questions asking for specific technical solutions about neural networks and genetic algorithms. I agree with Ben that we need to make this site different and start migrating all these questions to other sites, where there *is already* an answer to most of them.
Why would we want to ask them again?
(apart from rush for reputation)
Upvotes: 3 <issue_comment>username_3: I'm going to say "yes". That doesn't mean we need to *solicit* those kinds of questions, but if / when they show up, I think we should just handle them "organically" if you will. That is, up/down vote them, answer them, comment on them, etc., exactly as we would anything else. I don't see any point in us taking on the effort of cross-checking with other sites and migrating questions, etc. IF the SE infrastructure makes it super easy to do some in some cases, then sure, fine, I guess. But I oppose having ai.se mods waste their energy and time dealing with pedantic quibbling over which site is "most" appropriate for a question.
Upvotes: 2 <issue_comment>username_4: **Yes**
I am sorry to be the one who posts Yes, but as we are in the beta, I want to be straight forward.
In addition to that, AI is also on-topic in the CS site. [I was the one who raised this in the definition phase](https://area51.meta.stackexchange.com/q/22939/142759).
So, a lot of topic which this site aims to cover are already covered in the existing sites.
Upvotes: 3 <issue_comment>username_5: [@RobertCartaino suggested in this post](https://ai.meta.stackexchange.com/a/72/8) that:
>
> "programming" and "implementation problems" be explicitly listed as outside the scope of this site
>
>
>
in order to direct the authors to sites which were explicitly created to handle these "technical" issues.
This site failed already two times, because people didn't ask the right questions and most of them were already covered by somewhere else (e.g. Stack Overflow, Statistics, Data Science, and similar applied sites).
Basically:
>
> Data Science is an applied site for all the programmers/statisticians/mathematicians who are trying to make this stuff work.
>
>
> a more-comprehensive site which included the development of AI, machine learning, statistical tools, big data, NLP, data mining, etc,
>
>
>
so:
>
> No, machine learning as far as implementation goes is not on topic for this site.
>
>
>
and:
>
> if this site were to simply start reiterating the implementation/tools questions that are already covered elsewhere, this site will not likely make it out of private beta.
>
>
>
---
On the [other hand](https://area51.meta.stackexchange.com/questions/24014/will-machine-learning-be-considered-as-on-topic/24016#comment38287_24016):
>
> Everything in the proposal is considered when evaluating whether the site would likely be viable. If the proposal looks good across the board, that is the "compelling case"
>
>
>
Upvotes: 2 <issue_comment>username_5: I believe questions asked at [Stats.SE](https://stats.stackexchange.com/) about [artificial intelligence](https://stats.stackexchange.com/questions/tagged/artificial-intelligence) should be on-topic here as well, because:
* since past 6 years there were only [~73 questions asked about AI](https://stats.stackexchange.com/questions/tagged/artificial-intelligence), 1/3 of them still [unanswered](https://stats.stackexchange.com/questions/tagged/artificial-intelligence?sort=unanswered),
* 40% of question about [machine-learning](https://stats.stackexchange.com/questions/tagged/machine-learning) are also [unanswered](https://stats.stackexchange.com/questions/tagged/machine-learning?sort=unanswered), try scrolling.
You may suggest they may lacking of AI experts there, so lets move there. However not all AI experts are using or are interested in statistics models with AI.
For example I'm no where near as statistician, I've no idea about cross-validation aka rotation estimation models, but I may use and implement practical AI algorithms.
Therefore I think our site has already its own distinct and unique scope in comparison to Stats.SE, because it is about pure Artificial Intelligence and beyond.
You can still asks about AI at Stats.SE, but it should be focused to *statistical learning*. To support that, [check this post](https://stats.meta.stackexchange.com/a/2095/12989):
>
> Question on AI including a comparison with statistical learning would be pretty clearly on topic here.
>
>
>
They were accepting even without that, but I think most likely because people didn't have the right place to ask. If they've asked, didn't have much attention (maybe AI experts aren't interested in statistical models).
If you've question about theoretical AI, you can consider asking at: [CSTheory.SE](https://cstheory.stackexchange.com/questions/tagged/ai.artificial-intel) (not active either).
We can only hope that after [6 years](http://blog.stackoverflow.com/2010/12/no-artificial-intelligence-in-area-51/) of previous failures, we're able to break some ice this time.
We've one-time final opportunity to not have AI spread across the whole network:
Stats.SE, CSTheory.SE, CogSci.SE, Philosophy.SE, Worldbuilding.SE, SO.SE, CS.SE, HSM.SE, Robotics.SE, GameDev.SE, gosh where else, with no real AI experts in one place.
So basically the goal of this site is as pointed by [@lejlot](https://area51.meta.stackexchange.com/questions/11658/faked-artificial-intelligence-like-in-game-development#comment18885_11709):
>
> To bring people from this one particular field, which exists in
> between all above in one place. I see the reason behind it - as now
> questions regarding AI are scattered across these sites and get very
> little attention from actual experts, who also visit just a subset of
> these. Additionally - on each site these questions are tagged in a
> different way, so it is impossible to track them. Unification (new
> site) would make all of it much easier (and in fact - possible for the
> first time).
>
>
>
If this going to fail this time, people still will have to have 10-20 different accounts to ask the right questions on the right sites (which is very inconvenient). This would be very sad.
---
To summary, [some say](https://www.quora.com/I-once-heard-statistical-learning-is-not-the-path-to-AI-Artificial-Intelligence-what-are-the-arguments-that-support-this-statement-claim):
>
> statistical learning is not the path to AI (Artificial Intelligence)
>
>
>
but it's open to debate.
Upvotes: 2
|
2016/08/02
| 915
| 3,850
|
<issue_start>username_0: I'm seeing a lot of answers from people along the lines of "AI is just bits and bytes and ultimately cannot be smarter than its creator because its creator would have to use their brain to make something smarter than themselves, which isn't possible."
It's kind of baffling to me to see these answers, especially in regards to the singularity, on a forum dedicated to AI. There is already image recognition that can recognize objects more accurately than humans, IBM's Watson can diagnose lung cancer at a rate much more accurately than human physicians, and Google's Alpha Go beat the Go world champion, even while experts were predicting that AI wouldn't succeed at doing this for another 10 years.
At the same time, I am completely certain that any of the individual programmers of Alpha Go would not have succeeded in defeating the Go champion of the world. I'm also fairly certain that the Watson programmers would not do better than Watson or a human physician at identifying lung cancer. These are already cases of the AI being more intelligent than its programmer, albeit in domain-specific cases.
Therefore, it seems wholly lazy and uncreative for people to provide such answers that AI cannot be more intelligent than a single creator and therefore human-level AI and beyond is not possible. I think it does not contribute to the discussion.<issue_comment>username_1: If an answer is wrong, it should be downvoted, plain and simple. Clearly we want to discourage wrong information, and downvotes are designed to point out incorrect, irrelevant, or otherwise poor content. You seem to have really good examples that show such answers are wrong, so please feel free to mention them in a comment when downvoting!
Upvotes: 4 [selected_answer]<issue_comment>username_2: >
> I'm seeing a lot of answers from people along the lines of "AI is just bits and bytes and ultimately cannot be smarter than its creator because its creator would have to use their brain to make something smarter than themselves, which isn't possible."
>
>
>
I think this argument is a bit unclear and needs some refinement. It is true that AI can indeed be smarter than the creator at certain tasks (AlphaGo being better at Go than the programmers of AlphaGo, for instance). What I think this argument is really saying is:
>
> "AI is just bits and bytes programmed by its creator. The creator would be able to *know* how the AI works, otherwise he would be unable to create it in the first place. Therefore, the creator can be said to be *superior* to that of its creation, since the creator can understand its creation."
>
>
>
That seems like a more logical premise. Sure, AlphaGo is better at Go than the programmers of AlphaGo, but AlphaGo's programmers actually knows how AlphaGo operates. This type of argument was made in the paper [Creativity, the Turing Test, and the (better) Lovelace Test](http://kryten.mm.rpi.edu/lovelace.pdf), which specifically argues that AIs cannot be creative since programmers are able to figure out what their creations (AIs) are doing. Another paper ["The Lovelace 2.0 Test of Artificial Creativity and Intelligence"](http://arxiv.org/pdf/1410.6142v3.pdf) saw this argument as so self-evidently true that it tried to create a weaker version of the Lovelace Test to identify and measure AI creativity.
The programmers, basically, know how their program works. That doesn't mean the program is less intelligent than the programmers. Just that the programmers can understand why their programs behave the way they do, given enough time and patience.
Either way, I would not support discouraging answers such as these, if only because this view does have support within the AI scholarly community. If you have experts who hold this view, then we should let this view be given exposure.
Upvotes: 2
|
2016/08/02
| 235
| 829
|
<issue_start>username_0: The latter is the canonical way to refer to the field, and its unclear when, if ever, [deep-network] would be preferable. Its a small change, but it'd help avoid very odd sounding questions like ["What is Deep Network?"](https://ai.stackexchange.com/q/96/109)<issue_comment>username_1: I would say yes. I don't know many people who use the term "deep network" like that. You may hear "deep neural network", but that's still basically synonymous with "deep learning" as far as I can tell.
Upvotes: 2 <issue_comment>username_2: If `deep-learning` is preferred, then `deep-network` should be set up as a [tag synonym](https://meta.stackexchange.com/a/70718/135236) for it, that way if anyone tries to use it, it gets mapped to the preferred name. We need someone with 1250 reputation to do that.
Upvotes: 1
|
2016/08/02
| 479
| 2,004
|
<issue_start>username_0: During the private beta we have the opportunity to send Emails via stack exchange:
[](https://i.stack.imgur.com/2c4CE.jpg)
And because stackexchange is already well-known on the net, it is more probable that our invitation will be read and clicked on. And I don't think there would be any academic mail server which rejects mail sent by the domain stackexchange.com.
As you know [there are a lot of artificial intelligence related journals](http://www.scimagojr.com/journalrank.php?category=1702), I want to see if it is useful or allowed to use the emails of some of those young researchers who have published papers in this journals recently and introduce them this new site?
Because my friends or the people that I have met directly will always notice the emails sent by me personally but a stranger may consider it a spam.<issue_comment>username_1: Certainly, asking real AI researchers to join would be great!
Paper authors include their e-mail addresses in their publications exactly for the purpose of being contacted about their work. I'm sure it would bring most students great happiness to know that their work has been noticed.
Students who aren't terribly busy will probably be willing to read all the e-mails they receive in their academic/professional e-mail inboxes, no matter whether the messages from from an `@stackexchange.com` address or a personal address. Indeed, composing a personal (non-automated) message mentioning how you enjoyed a paper would be appreciated, even if the person doesn't have the time or inclination to check out our site.
Upvotes: 4 <issue_comment>username_2: Yes, that sounds like an excellent idea to me.
Upvotes: 2 <issue_comment>username_3: Technically I guess you could, but I think it would be fair to add some warnings such as the site might closed, and questions on Stack Exchange are sometimes deleted or closed for moderation reason.
Upvotes: 2
|
2016/08/02
| 456
| 2,004
|
<issue_start>username_0: I asked a question that was meant to discuss artificial intelligence in general. I tagged it [artificial-intelligence](https://ai.stackexchange.com/questions/tagged/artificial-intelligence "show questions tagged 'artificial-intelligence'"), and someone fairly pointed out that that's redundant. I changed it to [agi](https://ai.stackexchange.com/questions/tagged/agi "show questions tagged 'agi'"), because the question referred specifically to how [optimization](https://ai.stackexchange.com/questions/tagged/optimization "show questions tagged 'optimization'") applies to artificial intelligence, but I'm not sure that was right.
Should the [agi](https://ai.stackexchange.com/questions/tagged/agi "show questions tagged 'agi'") tag refer only to questions that reference Artificial General Intelligence specifically, or can it be used for questions that could be related to AGI in more indirect ways?<issue_comment>username_1: Certainly, asking real AI researchers to join would be great!
Paper authors include their e-mail addresses in their publications exactly for the purpose of being contacted about their work. I'm sure it would bring most students great happiness to know that their work has been noticed.
Students who aren't terribly busy will probably be willing to read all the e-mails they receive in their academic/professional e-mail inboxes, no matter whether the messages from from an `@stackexchange.com` address or a personal address. Indeed, composing a personal (non-automated) message mentioning how you enjoyed a paper would be appreciated, even if the person doesn't have the time or inclination to check out our site.
Upvotes: 4 <issue_comment>username_2: Yes, that sounds like an excellent idea to me.
Upvotes: 2 <issue_comment>username_3: Technically I guess you could, but I think it would be fair to add some warnings such as the site might closed, and questions on Stack Exchange are sometimes deleted or closed for moderation reason.
Upvotes: 2
|
2016/08/02
| 3,379
| 9,552
|
<issue_start>username_0: I was going to answer a question about reinforcement learning and wanted to show some formulas using the same notation I use on CrossValidated, for instance:
$r\_{t+1}+\gamma \max\_a Q(s\_{t+1},a)$
But it is currently not supported, at least the way I tried it. Can we have support for LaTeX formatting here?
Examples:
* [What artificial intelligence strategies are useful for summarization?](https://ai.stackexchange.com/q/157)<issue_comment>username_1: While it might be nice to have for some questions, most questions you would need LaTeX for should be off-topic here. This site is not meant for machine learning questions, as Cross Validated and Data Science Stack Exchange sufficiently cover those subjects.
See: [Are all questions asked on stats and data science SE also on topic here?](https://ai.meta.stackexchange.com/questions/4/are-all-questions-asked-on-stats-and-data-science-se-also-on-topic-here?cb=1)
>
> **Note:** I posted this answer when I didn't know very much about AI, and I have misunderstood or missed some of the parts of AI that should be on-topic here, I am now of the opinion that we should have LaTeX here. I'll leave this answer here because of the votes (and vote balance) on it, but I don't agree myself anymore with it. So please count an extra downvote from me.
>
>
>
Upvotes: 2 <issue_comment>username_2: I think we should discourage the use of LaTeX, but should allow it. Our goal is to attract experts in AI, and the language of AI (today) is math. Like that post in the OP (which I wrote, btw), I think math makes a lot of concepts easier to understand.
I think this SE should focus on the *design* aspects of AI and AI research instead of the programming and libraries (those questions should go to Data Science) or the statistics (those should go to Cross Validated), but some mathematics is often a core component of AI theory.
Upvotes: 3 <issue_comment>username_3: Yes, absolutely. Regardless of your position on the whole "theory vs. implementation" thing, math is an essential part of AI and having convenient access to LaTex would be a boon here.
Upvotes: 5 <issue_comment>username_4: Here are several questions and answers that would benefit from MathJax support on this website. These are just a few examples I've found in a 5 minutes search. Nevertheless, I think this number is enough to justify a MathJax support on this website.
### Questions
* ~~https://ai.stackexchange.com/a/4710/2444~~
* ~~https://ai.stackexchange.com/a/2994/2444~~
* ~~https://ai.stackexchange.com/q/4085/2444~~
* ~~https://ai.stackexchange.com/q/3758/2444~~
* ~~https://ai.stackexchange.com/q/4740/2444~~
* ~~https://ai.stackexchange.com/q/4296/2444~~
* ~~https://ai.stackexchange.com/q/4140/2444~~
* ~~https://ai.stackexchange.com/q/2226/2444~~
* ~~https://ai.stackexchange.com/q/2865/2444~~
* ~~https://ai.stackexchange.com/q/3458/2444~~
* ~~https://ai.stackexchange.com/q/113/2444~~
* ~~https://ai.stackexchange.com/q/5580/2444~~
* ~~https://ai.stackexchange.com/q/13577/2444~~
* ~~https://ai.stackexchange.com/q/5075/2444~~
* ~~https://ai.stackexchange.com/q/8240/2444~~
* ~~https://ai.stackexchange.com/q/3226/2444~~
* ~~https://ai.stackexchange.com/q/5527/2444~~
* ~~https://ai.stackexchange.com/q/6009/2444~~
* ~~https://ai.stackexchange.com/q/5825/2444~~
* ~~https://ai.stackexchange.com/q/9226/2444~~
* ~~https://ai.stackexchange.com/q/5638/2444~~
* ~~https://ai.stackexchange.com/q/5606/2444~~
* [How to implement exploration function and learning rate in Q Learning](https://ai.stackexchange.com/q/5332/2444)
* [Genetic Algorithm - creatures in 2d world are not learning](https://ai.stackexchange.com/q/6366/2444)
* [How to perform back propagation with different sized layers?](https://ai.stackexchange.com/q/20053/2444)
* [How to determine the probability of an "existence" question](https://ai.stackexchange.com/q/2462/2444)
* [How do I translate these English sentences into first-order logic without quantifiers?](https://ai.stackexchange.com/q/2863/2444)
* [GA rule discovery fitness function](https://ai.stackexchange.com/q/3040/2444)
* [Is random initialization of the weights the only choice to break the symmetry?](https://ai.stackexchange.com/q/6789/2444)
* [Matrix Dimension for Linear regression coefficients](https://ai.stackexchange.com/q/6990/2444)
### Answers
* ~~https://ai.stackexchange.com/a/1927/2444~~
* ~~https://ai.stackexchange.com/a/4227/2444~~
* ~~https://ai.stackexchange.com/a/2292/2444~~
* ~~https://ai.stackexchange.com/a/4185/2444~~
* ~~https://ai.stackexchange.com/a/4388/2444~~
* ~~https://ai.stackexchange.com/a/3906/2444~~
* ~~https://ai.stackexchange.com/a/267/2444~~
* ~~https://ai.stackexchange.com/a/3162/2444~~
* ~~https://ai.stackexchange.com/a/6280/2444~~
* ~~https://ai.stackexchange.com/a/5620/2444~~
* ~~https://ai.stackexchange.com/a/5079/2444~~
* ~~https://ai.stackexchange.com/a/2300/2444~~
* ~~https://ai.stackexchange.com/a/4479/2444~~
* ~~https://ai.stackexchange.com/a/5597/2444~~ (post deleted)
* ~~https://ai.stackexchange.com/a/6983/2444~~
* ~~https://ai.stackexchange.com/a/13216/2444~~
* ~~https://ai.stackexchange.com/a/3507/2444~~
* ~~https://ai.stackexchange.com/a/13681/2444~~
* ~~https://ai.stackexchange.com/a/27411/2444~~
* ~~https://ai.stackexchange.com/a/5334/2444~~
* ~~https://ai.stackexchange.com/a/6172/2444~~ (post deleted)
* <https://ai.stackexchange.com/a/22731/2444>
* <https://ai.stackexchange.com/a/17651/2444>
* <https://ai.stackexchange.com/a/6323/2444>
* <https://ai.stackexchange.com/a/6628/2444>
* <https://ai.stackexchange.com/a/5607/2444>
* <https://ai.stackexchange.com/a/20899/2444>
* <https://ai.stackexchange.com/a/3510/2444>
* <https://ai.stackexchange.com/a/2546/2444>
* <https://ai.stackexchange.com/a/6017/2444>
* <https://ai.stackexchange.com/a/6093/2444>
* <https://ai.stackexchange.com/a/16127/2444>
* <https://ai.stackexchange.com/a/6999/2444>
* <https://ai.stackexchange.com/a/6991/2444>
* <https://ai.stackexchange.com/a/9993/2444>
* <https://ai.stackexchange.com/a/6794/2444>
* <https://ai.stackexchange.com/a/10995/2444>
* <https://ai.stackexchange.com/a/6639/2444>
Upvotes: 4 <issue_comment>username_5: I, for one, would love its inclusion. I do not believe it is possible to divorce AI from mathematics on many levels. For instance, I wanted to ask a question regarding the use of backpropagation with regards to the ANFIS model but had to do so in a clumsy way as I was not able to include the proper notation for partial derivatives. It would surprise me to think that this site is just for "high level" philosophical discussions on AI.
Upvotes: 3 <issue_comment>username_6: **Starting a new list of math questions to expand on [nbro's list](https://ai.meta.stackexchange.com/a/1319/1671):**
* ~~https://ai.stackexchange.com/questions/6633/back-propagation-in-nn-with-sigmoid-activation-function-division-by-0~~ (post deleted)
* ~~https://ai.stackexchange.com/questions/5057/k-armed-bandit-and-reinforcement-learning~~
* ~~https://ai.stackexchange.com/q/7032/1671~~
* ~~https://ai.stackexchange.com/questions/7147/gradient-of-boltzmann-policy-over-reward-function~~
* ~~https://ai.stackexchange.com/questions/7182/small-multinomial-naive-bayes-text-classification-probabilities~~
* ~~https://ai.stackexchange.com/questions/7207/mathematical-modelling-of-a-i-algorithms~~
* ~~https://ai.stackexchange.com/questions/6308/linucb-with-hybrid-linear-models~~
* ~~https://ai.stackexchange.com/questions/1925/are-ffnn-mlp-lipschitz-functions~~
* [How does this sigma work?(Harris algorithm)](https://ai.stackexchange.com/questions/6914/how-does-this-sigma-workharris-algorithm)
* [Defining formula for fuzzy equation](https://ai.stackexchange.com/questions/6640/defining-formula-for-fuzzy-equation)
* [How to calculate gradient of filter in convolution network](https://ai.stackexchange.com/questions/6030/how-to-calculate-gradient-of-filter-in-convolution-network)
* <https://ai.stackexchange.com/a/5380/2444>
* <https://ai.stackexchange.com/a/5179/2444>
* [Simple question about HS algorithm's formul(Optical flow)](https://ai.stackexchange.com/questions/6995/simple-question-about-hs-algorithms-formuloptical-flow)
* <https://ai.stackexchange.com/a/7034/1671>
* [Why do we have to solve MDP in each iteration of Maximum Entropy Inverse Reinforcement Learning?](https://ai.stackexchange.com/q/7003/1671)
* [Matrix Dimension for Linear regression coefficients](https://ai.stackexchange.com/questions/6990/matrix-dimension-for-linear-regression-coefficients)
* <https://ai.stackexchange.com/a/7103/2444>
Upvotes: 2 <issue_comment>username_7: I would like to add to the calls for LaTeX support with a specific topic.
In my opinion, the AI Stack Exchange should be **the** home for questions about *Reinforcement Learning*.
RL questions actually appear in larger numbers on Data Science and Cross Validated Stack Exchange sites. That makes little sense to me, when AI, robotics and other better homes in a conceptual sense exist for this topic.
RL is a technical subject requiring solid understanding of underlying maths, especially for anyone wanting to engage in algorithm design. I would like to be able to write equations and maths-based pseudo code when writing questions or answers about RL. It is a shame that this site presents a barrier to doing that. Along with the larger audience for other Stack Exchange sites, this one is losing out IMO on a current hot topic that could provide much traffic. And in part that is due to barriers when writing content.
Upvotes: 2
|
2016/08/02
| 908
| 3,285
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<issue_start>username_0: We have a [chatroom](//chat.stackexchange.com/rooms/43371/artificial-intelligence). At the moment it doesn't really have a name. Other sites' chatroom names include:
* Super User's "Root Access"
* PPCG's "The Nineteenth Byte"
* Blender's "The Renderfarm"
* Pets' "The Litterbox"
* Travel's "You Are Here"
* Aviation's "The Hangar"
So, what should we call ours?
While we're at it, what should we name our resident feed bots (Main and Meta)?<issue_comment>username_1: Turing Testing Room
===================
A play on the term "Turing test" (an examination of how well a machine mimics natural conversation with a human): tests taken by human students are usually administered in a testing room.
Questions on the main site are currently posted to the ticker, so we don't see the username, but if that's changed, it could be called **[Multivac](https://en.wikipedia.org/wiki/Multivac)** after the computer from some of Asimov's stories. We could call the meta bot **[Watson](https://en.wikipedia.org/wiki/Watson_(computer))**.
Upvotes: 3 <issue_comment>username_2: Automata
========
Study of abstract machines as well as the computational problems that can be solved using them.
Upvotes: 2 <issue_comment>username_2: The Thought
===========
>
> Artificial intelligence is based on the assumption that the process of human **thought** can be mechanized.
>
>
>
Upvotes: 2 <issue_comment>username_3: **The Singularity**
-------------------
I probably don't need to explain that :-)
And for the bots, how about Daneel and Giskard?
Upvotes: 4 <issue_comment>username_4: Searle's Room
=============
Bots: Meta & Cognition
Upvotes: 2 <issue_comment>username_5: **The nth layer**
=================
This would be about deep learning which is about multiple layers of neurons. So, as DL has been very hot in the domain currently, I think this name would be appropriate.
Upvotes: 2 <issue_comment>username_6: Replicants
==========
As in Blade Runner. And HAL and Computer for the bots.
Upvotes: 2 <issue_comment>username_7: **Electric sheep**
I think everyone knows this, just in case: [wiki link](https://en.wikipedia.org/wiki/Do_Androids_Dream_of_Electric_Sheep%3F)
Upvotes: 2 <issue_comment>username_8: The Chinese Room
================
A reference to the [Chinese Room Argument](https://en.wikipedia.org/wiki/Chinese_room).
We would need to make it clear that we're separate from [Chinese.SE](https://chinese.stackexchange.com) though...!
One of the bots could be named Searle, who invented the thought experiment.
Then we really have a Searle getting inputs and producing outputs, just as in the thought experiment.
Upvotes: 3 <issue_comment>username_8: Back Propagation
----------------
A reference to backpropagation neural networks. We could use this name because in our chatroom, ideas will be propagated back and forth.
Upvotes: 2 <issue_comment>username_2: ### The early stopping
>
> Form of regularization used to avoid overfitting when training.
>
>
>
See: [What is early stopping?](https://ai.stackexchange.com/q/16/8)
Upvotes: 1 <issue_comment>username_2: The Dropout
===========
>
> A technique of reducing overfitting in neural networks. The term "dropout" refers to dropping out units in a neural network.
>
>
>
Upvotes: 0
|
2016/08/02
| 1,611
| 6,356
|
<issue_start>username_0: A core goal of the private beta is to generate high-quality content that will attract experts. We are also given the opportunity to invite experts by email to the private beta. My question is simple: exactly what kind of experts are we trying to attract?
According to [this question](https://ai.meta.stackexchange.com/questions/4/are-all-questions-asked-on-stats-and-data-science-se-also-on-topic-here?cb=1) , data science and the *implementation* of artificial intelligence are off-topic. The problem is that we don't want to become a duplicate of Stats or Data Science SE. The question links to [this answer](https://area51.meta.stackexchange.com/questions/24014/will-machine-learning-be-considered-as-on-topic/24016#24016) on Area 51 which says that this site is for questions in the "academic humanities arena". This seems to suggest that we want experts in academic humanities.
However, most experts in the field of artificial intelligence *are experts of implementation*. They are applied mathematicians and computer scientists who are trying to make artificial intelligence a reality. The recent advances in artificial intelligence, like [Alpha Go](https://deepmind.com/alpha-go), have been the result of breakthroughs in implementation.
If this site is about humanities-style questions about Artificial Intelligence, then what appeal does it have to the type of people who created Alpha Go, who are primarily computer scientists and mathematicians? I'm not convinced they have special expertise about the ramifications of Artifical Intelligence on human society, politics, law, etc.
Perhaps we need to redefine what this site is about. I think a place to look for inspiration is Math SE and MathOverflow. One is about mathematics at any level, while the other is a site for research level mathematicians. Maybe Artificial Intelligence SE should be to Data Science SE and Stats SE what MathOverflow is to Math SE. That is, it should be a site about tackling research level AI problems with the tools of data science and statistics.
This means that we'll have to seriously elevate the quality of our questions and answers to attract real AI experts. But at least we'll have experts to attract.<issue_comment>username_1: First up, when I posted [my answer to the question you reference](https://ai.meta.stackexchange.com/a/7/75), I was just passing along the information given to us by <NAME>. I'm not wedded to that opinion.
I think all the scientists working on AI would be helpful here even though we're not working on implementation. This is what the original Area 51 Discussion post said (excerpted):
>
> Data Science is an *applied* site for all the programmers/statisticians/mathematicians who are trying to make this stuff *work*.
>
>
>
There's some leeway there. Specifically, technical questions seem to be OK, as long as they're not super in depth about the math or programming. There are also "why" questions (as opposed to "how") that are very interesting and educational. I like [this question](https://ai.stackexchange.com/q/92/75) a lot. Scientists are welcome.
We don't *have* to limit ourselves to the philosophy and practical effects of AI, though they're in scope. Philosophers are welcome too.
Upvotes: 3 <issue_comment>username_2: First there is a need to distinguish modeling from implementation. They are not exactly the same, although strongly related. This was a very difficult lesson to learn among mathematicians and early programmers, notably in the 70s (mathematical proofs can demand a lot of non-trivial programming work to make them "computable", as in runnable on a computer).
As for Machine Learning (by far the most active AI category), modeling belongs to Data Science SE---perhaps the one thing that most people agree on. Implementation should be out of there, as the issues and focus differ (but again, they are related).
Now, should implementation issues be in AI SE, or StackOverflow? The recurring example is TensorFlow, who's home page states that questions should go to StackOverflow. And we should respect that...
But we should keep in mind that the TensorFlow team will choose SO, because it is the largest community, and because the team has something else to do rather than experimenting with hardly visible communities. Well, size matters. We may think that if AI SE becomes big enough on the implementation side, the TensorFlow team (and other major frameworks) may move actually.
In fact, I think now that implementation questions would benefit from a dedicated site (my view has evolved since the Area 51 definition phase). I have replied and tried to reply to several SO questions related to ML tools, and I think some are out of place compared to other questions. For example, [some](https://stackoverflow.com/questions/38321024/why-this-simple-tensorflow-code-is-not-successful-convnetjs-using-tensorflow/38368469#comment64172189_38368469) TensorFlow questions are not really programming questions, and not really framework questions. I mean, there is background knowledge on graph construction and execution, as well as background knowledge about statistics and probabilities that are really necessary to make meaningful contributions.
This is not to say that *all* questions are out of place on SO. [Some](https://stackoverflow.com/questions/38297581/tensorflow-gpu-utilization-is-almost-always-at-0#comment64124967_38297581) are *really* framework issues or (Python) programming issues, and they are good there.
Based on this opinion, I think the site should be interested in implementation experts, whether they work on ML or Expert Systems (or both?).
See also some threads on Area 51 like [this one](https://area51.meta.stackexchange.com/questions/23789/the-example-questions-will-not-attract-experts) and [this one](https://area51.meta.stackexchange.com/a/23528/69948).
Upvotes: 4 [selected_answer]<issue_comment>username_3: For FSM's sake, not this again. Please, no... stop with the "let's attract experts" verbiage. I mean, don't get me wrong.. of course we *want* experts, but we don't want *only* experts and we don't want to anoint "experts" with some special degree of relevance. This is a HUGE part of what made it so hard to have a successful ai.se before... we chased away the good, in pursuit of the perfect.
Upvotes: -1
|
2016/08/03
| 321
| 1,125
|
<issue_start>username_0: Is it AI or A.I., or both abbreviations are fine? Basically, with the dots or without?<issue_comment>username_1: In British English it has to be "AI".
In American English it can be both "AI" and "A.I.".
Sources:
* <http://www.oxforddictionaries.com/us/words/punctuation-in-abbreviations-american>
* Oxford A–Z of Grammar and Punctuation by <NAME>.
* <https://en.wikipedia.org/wiki/Full_stop#Abbreviations_and_personal_titles_of_address>
Upvotes: 2 <issue_comment>username_2: To be honest, I've never seen it written "A.I.", but both look fine to me. If somebody wants to use the dots, more power to them. As username_1 showed, it's kind of dependent on whether a person is using British or American English. Suggested edits that only change stylistic things like this should be rejected; let the post author choose as long as it's consistent within a post.
If there is ever a similar question about tag names, the official policy is that the American style should be used. (SE is an American company.)
Source: [Meta Stack Exchange](https://meta.stackexchange.com/a/23873/295684)
Upvotes: 2
|
2016/08/03
| 353
| 1,500
|
<issue_start>username_0: There are two tags: [quantum-computers](https://ai.stackexchange.com/questions/tagged/quantum-computers "show questions tagged 'quantum-computers'") and [quantum-computing](https://ai.stackexchange.com/questions/tagged/quantum-computing "show questions tagged 'quantum-computing'"). Some question were moved from computing to computers.
Which tag should be the main one?
I think 'quantum computers' sounds more like hardware questions, and 'quantum computing' is a verb which is about using quantum computers for computation.
Which tag should be used then for asking AI questions? Or make another the synonym of it?<issue_comment>username_1: I'd (personally) go for **computing** because it is about doing things with computers rather than the computers themselves, as you state in the question yourself.
Upvotes: 1 <issue_comment>username_2: I consolidated the tags to [quantum-computing](https://ai.stackexchange.com/questions/tagged/quantum-computing "show questions tagged 'quantum-computing'") because this is not an *applied* hardware and programming site.
A tag synonym isn't really appropriate here. Synonyms were intended to link two completely separate words meaning essentially the same thing (think 'car' vs 'auto'). For simple variations on the *same* word, there's no need to bulk up the tag listings with every word inflection. Text completion will help guide the user to the correct usage:
`q``u``a``n` → `quantum-computing`
Upvotes: 4 [selected_answer]
|
2016/08/03
| 724
| 2,888
|
<issue_start>username_0: AI is a bloated term---we are facing this since day 1 of the definition stage. There are already quite a few questions going beyond the original (blurry) boundary of the proposal, notably on implementation issues.
But the worst problem seems to be the lack of objectivity in answers, and sometimes in questions too.
I will single out this [question](https://ai.stackexchange.com/questions/111/how-would-self-driving-cars-make-ethical-decisions-about-who-to-kill) at time of reading, but there are already several like this one.
We must avoid too many threads that lack objectivity. I intend to vote down answers that are too subjective (but, well, I cannot down vote infinitely, as you know), and comment as necessary. Scalability issue, even in this private beta.
What would be the best way to proceed?<issue_comment>username_1: The question you link is a perfectly valid question in the philosophy of artificial intelligence. Philosophy is the other large part of AI, together with technology, so they should be on-topic here.
However, one should be careful when answering these questions, that one does not base the answer on own opinions. One should reference what philosophers have said in the past, like one of the answers on the question you link mentions the Trolley problem.
Upvotes: 2 <issue_comment>username_2: During this private beta, you actually can downvote infinitely - the minimum rep for that privilege in this stage is 1. I think we're still subject to the ["upvote one thing for every two things you downvote"](https://blog.stackoverflow.com/2010/03/important-reputation-rule-changes/) rule, though, but that shouldn't be limiting, especially considering you have to have cast 300 votes before it takes effect.
It looks like you've already figured out what to do with nonconstructive answers and questions: downvote. For answers, you'll take a little hit of 1 point, but if it means saving the site from drivel, that's a fine price to pay. Questions that can *only* be answered subjectively can be closed as primarily opinion-based.
Upvotes: 2 <issue_comment>username_3: If you don't like a question, down-vote it. That said, I disagree with the premise that there's a problem and "ZOMG, s0meth1ng mus7 b3 d0ne, won'7 s0mebody th1nk of th3 ch1ldr3n1?!??!???"
You can't dictate through top down command and control how a community should behave. Just because the powers-that-be at StackExchange say "no subjective questions" doesn't mean that we need to reflect that and get all up in arms over any question that allows from an element of subjectivity. The community will be what the community is, quit trying to social-engineer it.
>
> There are already quite a few questions going beyond the original (blurry) boundary of the proposal, notably on implementation issues.
>
>
>
Then the original boundary was wrong.
Upvotes: -1
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2016/08/03
| 889
| 3,285
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<issue_start>username_0: Today, I was looking at the oldest questions asked in other sites. Take **Geographic Information Systems** as an example:
[The site's age is 6y1m](http://stackexchange.com/sites#technology-oldest) and and as it is seen in [the area51 page of the site](http://area51.stackexchange.com/proposals/1425):
* [The definition phase has started on June 1th 2010.](http://area51.stackexchange.com/posts/1425/revisions)
* [The Commitment phase has started on June 14th 2010.](http://area51.stackexchange.com/proposals/1425?page=54&phase=commitment&committers=mostrecent#tab-top)
* [The private beta phase has started on July 22th 2010.](http://area51.stackexchange.com/proposals/1425?page=1&phase=commitment&committers=mostrecent#tab-top)
And because that time the private betas last for only one week, probably the public beta started on July 29th 2010.
If you take a look to the oldest questions, you'll see that some of them have been asked even before July 22th 2010. [like this one which has been asked on August 9th 2009 and has been migrated from stackoverflow.com to GIS.SE.](https://gis.stackexchange.com/q/15541/19874)
Also if you cast a glance to [questions asked before July 29th 2011](https://gis.stackexchange.com/questions?page=1431&sort=newest), you'll see that some of them has been migrated from another sites like superuser.com, etc.
I wanna see if you're going to migrate some questions from other sites to here in private beta?
Or it should be done after getting assured that private beta has ended successfully?
And how will the migration take place?<issue_comment>username_1: Migration to and from this site, in private beta, is most likely not going to be done. You'd have to invite people to the community in order for them to see the question - and when it comes to migrating from this site, it's easier to just close and re-ask (provided there are no answers yet).
After private beta... well, I suppose you could post a comment on such an Stack Overflow question that their question might be better off at ai.stackexchange. But those would have to be some good questions, and they'd have to be served here better than at Stack Overflow.
As for the example question, I think such a migration wouldn't be helping all that much - it's already answered, and as you can see, after migration, not much else happened to the question. It seems it was moved because both the asker and the answerer have an established presence on the other site, and because it fits better there.
Migration is not something to do quickly.
Upvotes: 1 <issue_comment>username_2: No, that wouldn't happen. A site only becomes eligible as a migration target from other sites' close dialogs after it loses the "beta" label entirely. Also, questions older than 60 days [cannot be migrated](https://meta.stackexchange.com/a/156255/295684), even by moderators! The migration you mentioned took place before that rule was instated.
Besides, a question being on-topic at the target site is not a sufficient reason to migrate it. It would have to be explicitly off-topic on the source too. (There's an exception for question owners who want their unanswered question moved: they can flag their post with a custom reason requesting migration.)
Upvotes: 3
|
2016/08/04
| 493
| 2,187
|
<issue_start>username_0: How should we as a site treat answers which are simply copy-pasted from another source, (whether with or without attribution)? Particularly those which show little understanding of the topic on the part of the poster.
I won't name anyone, but I've seen an answer where the user apparently simply copy-pasted the first paragraph of the first relevant google result, which didn't even really answer the original question. Afterwards, they admitted to know nothing about the topic themselves.
To me, this seems wrong. What is the general stance on this sort of answers?
(To the person in question, if they recognize themselves: Sorry about this, but I think this sort of thing needs to be discussed.)<issue_comment>username_1: Post consists almost entirely of content copied from elsewhere should NOT be considered a useful 'answer' in the context of this site.
Copying answers from external sources without permission is not allowed (and quoting or linking back to that site does ***not*** make that okay). Even posting an answer copied almost entirely from *reusable* content should be frowned upon, or even flagged to be removed.
This site was created to add something unique (and better) to the Internet. If we're simply copying stuff that's already out there, why bother? We're just adding another barrier between the folks searching for this stuff and the original source of the content.
Answers should create something original and useful for this community specifically. That is why we bring together individual communities of experts to host these topics.
And vetting is a ***big*** part of this site. Your *best* content should be rising to the top. **Please stop up-voting these posts!**
Upvotes: 3 <issue_comment>username_2: As long as it does answer the question, clearly indicates it is a quote, doesn't infringe licenses, and gives proper attribution, it is fine.
(Why reinventing the wheel?)
Upvotes: -1 <issue_comment>username_3: Plagiarism is unethical, IMHO: if you're providing a link to a source, it's more than enough. But if you want to provide *a cite*, then it must be referenced and marked up in appropriate manner
Upvotes: 0
|
2016/08/04
| 1,520
| 5,950
|
<issue_start>username_0: At one point I thought I got it, but then I lost again.
Few highlights:
* <https://ai.meta.stackexchange.com/a/46>
>
> modeling belongs to Data Science SE
>
>
> I think the site should be interested in implementation experts.
>
>
>
* <https://ai.meta.stackexchange.com/a/7>
>
> No, data science and the implementation of artificial intelligence are off-topic.
>
>
>
* <https://ai.meta.stackexchange.com/a/72>
>
> suggest that "programming" and "implementation problems" be explicitly listed as outside the scope of this site
>
>
>
Obvious points are:
* data science questions belong to [Data Science site](https://datascience.stackexchange.com/),
* programming questions belong [Stack Overflow](http://stackoverflow.com).
What about AI implementation and modelling? Above quotes are a bit contradictory.
So what's on-topic exactly, [AI modelling or implementation](https://ai.stackexchange.com/q/1297/8), or none of it?
If none of it, what should be?<issue_comment>username_1: Programming, algorithm, modeling, math, philosophy, and history questions should the off-topic, as they are already on-topic in [other SE](https://ai.meta.stackexchange.com/q/4/4), such as Stats and Data Science.
Data science and the Stats SE already have a huge overlap (>~80%), and I am worried to have a third SE that also significantly overlaps with them. Personally, it would further demotivate me to write any answer, as it gets tiring to copy-paste content, and updating duplicated answers is a pain.
Upvotes: 0 <issue_comment>username_2: I'm sorry, but we can't just go with a simple, blanket statement like "Programming, algorithm, modeling, math, philosophy, and history questions should the off-topic, as they are already on-topic in other SE, such as Stats and Data Science." Why? Because not *all* questions about "programming, algorithms, modeling...", vis-a-vis Artificial Intelligence, are on-topic at those other sites! But they are here.
And what's the distinction that should be in play? Well, simply, "programming, algorithms, modeling, math, etc. that are \*specific to AI" are on-topic here. It really can't be any other way.
I mean, think about it... we claim to be a "science" site, but then try to say that "math" is off-topic? That's absurd. Science *is* math and math *is* science. Or to put it another way "math is the language of science".
If we keep pushing this idea that all hard technical questions are off-topic, all we're going to get are vague questions about speculative aspects of AI, with answers that are nothing to speculation and hand-waving.
What should be on-topic? Questions about Artificial Intelligence, full-stop. It's right there in the name on the marquee sign, as they say.
Upvotes: 4 [selected_answer]<issue_comment>username_3: A for loop is not the same as gradient decent. Gradient decent is not the same as NN convergence, or generalization. You cannot do the latter without the former.
Biology is really Chemistry. Chemistry is really Physics. Physics is really math. If we required doctors to work through the math, then the quantum physics and molecular electronics, then the chemistry before they could do medicine they would die of old age first.
I think that we are trying to separate the fields of computer programming, data science, and such into layers of abstractions. Each layer has to be thick - to stand on its own and properly envelope its content.
Right now, Machine Learning and Artificial intelligence are "young" so there is going to be nuts and bolts. If we don't give clean bridges there then this area gets to be a philosophical wasteland - no engineering allowed. If we have some courtesy and we are willing to realize that the divisions are not clean yet, then we can make better mileage toward building a richer community.
Upvotes: 2 <issue_comment>username_4: Practical applications should be on topic here, at least at some extend to keep proportion between philosophy and implementations.
This is important in therms of building community. It is hard to change course later, and if you will this place to be one of fantasy-futurology-imaginary world building site of SE then strike out practical application.
this question could be asked on WB as well [Is consciousness necessary for any AI task?](https://ai.stackexchange.com/questions/1897/is-consciousness-necessary-for-any-ai-task) people there are very exited in discussing consciousness.
This question is definitely low quality <https://ai.stackexchange.com/questions/1869/deep-neural-network-for-not-so-popular-board-game> , for obvious reasons, fresh enthusiastic member with practical question - holding it discourages people who where fresh attracted, attracted by super title *Artificial Intelligence*, not boring *Data Science* where you do not know what to expect as Science of Data is big field. But there is short and clear AI, yes I wish one, give me two.
At the moment there is no implementations of AI(in movie sense)(known, for me, not a expert)
For that reason to keep track on the ground, practical application should be even if this site is intended to be subset of philosophy about AI.
Maybe change name then to reflect that - based on AI.SE I had expectation to see there useful stuff. From PAI.SE I expect nothing, not interested to know will AI kill humanity or not, how it will change perception of humanity about world, whatever.
At least amateur level implementation should be, at *least* it is bare minimum what you need.
Probably even that is not enough and will not work out. You should decide is that philosophy site or is that site about AI, if second then everything about AI(creation, theory, implementation, consequences) should be on topic here - all or nothing, have balls people, it is important for mankind, for our future.
You should discuss more which promises name promises - Artificial Intelligence - and whom it attracts.
Upvotes: 1
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2016/08/04
| 414
| 1,540
|
<issue_start>username_0: It was [suggested](https://ai.meta.stackexchange.com/a/72/8) that:
>
> "implementation problems" be explicitly listed as outside the scope of this site
>
>
>
Can we clarify what this could mean? Some example would be useful.
---
[@InquisitiveLurker](https://ai.meta.stackexchange.com/questions/1078/what-should-be-on-topic-modelling-or-implementation-or-anything-else#comment1065_1078) suggested that this could mean asking about inner workings of basic algorithms, but then how we define 'inner working'.
This also may help: [How to distinguish AI modeling from implementation?](https://ai.stackexchange.com/q/1297/8)
---
Any ideas?<issue_comment>username_1: Implementation problems may refer to the "how to do X with the Y tool/framework" kind of questions. Such kind of questions are indirectly related to AI, via the X part, which could lead to ask the OP to change the question focus. So questions that solely pertain to Y should be off-topic.
One issue with this approach, is that, say, 10 years ago, Y would have been seen as AI from science fictions. At some point in time, "we did it", and Y just looks like another tool.
Upvotes: 2 <issue_comment>username_2: Personally I disagree with the entire premise that "implementation should be off topic". I don't see any point in talking nothing but theory and never talking implementation. My fear is that that will lead us into fringe-land with a lot of sketch posts asking philosophical questions that aren't really helpful to anybody.
Upvotes: 2
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2016/08/04
| 1,396
| 5,174
|
<issue_start>username_0: In these early days, how can we attract attention to the best questions? The current front page does not accurately reflect this. Keeping in mind that our goal is to invite experts, I think it would be great if we could manually curate a list of questions that we can tout as ideal questions for this SE.
(We could create a community wiki here with the answers as we discuss how to proceed)<issue_comment>username_1: To give examples of questions I think are good, and that we should promote, in order with the best questions at the top:
* [How is it possible that deep neural networks are so easily fooled?](https://ai.stackexchange.com/questions/92/how-is-it-possible-that-deep-neural-networks-are-so-easily-fooled) I would not have put "easily" in the title, but it is an excellent question that the AI experts I know spend a lot of time thinking about.
* [How does Hinton's "capsules theory" work?](https://ai.stackexchange.com/questions/1294/how-does-hintons-capsules-theory-work)
* [Is Lisp still being used to tackle AI problems?](https://ai.stackexchange.com/questions/77/is-lisp-still-being-used-to-tackle-ai-problems)
* [What is the difference between MLP and RBF?](https://ai.stackexchange.com/questions/227/what-is-the-difference-between-mlp-and-rbf) : This can go to Crossvalidated but I'd argue it's out of place there and more at home here. Though it is a comparison of two specific algorithms, it reflects wider design issues in AI algorithms.
Others may disagree on this list, but I'd like to put up here the questions I think are more on-topic here than I think in other SEs. Some overlap is inevitable.
Upvotes: 1 <issue_comment>username_2: These are some ways to highlight and promote nice content on the site:
1. Organizing a quarterly post, where people are encouraged to post their favourite qns/ans and the top three would be awarded bounties by the mods or whoever is interested in contributing.
2. Cross-posting the nice ones to other sites like reddit, etc. This would help in marketing the site, as well as good karma by sharing good content.
Upvotes: 1 <issue_comment>username_3: I think that username_1's list is a good start if we want to get people who think of themselves as AI experts, instead of people who think of themselves as AGI experts. (The G is for 'general.') But in order to differentiate this site from Cross Validated or Data Science, we're trying to focus on the humanities / philosophy side.
I worry that this means that we're going to have a parade of AI 101 questions, like [How does multiple intelligences fit in AI?](https://ai.stackexchange.com/questions/179/how-do-multiple-intelligences-fit-in-ai) or [How does artificial intelligence Work in games?](https://ai.stackexchange.com/questions/1320/how-does-artificial-intelligence-work-in-games), which isn't an implementation or algorithms question because it's so broad and basic, or simple discussions of complicated issues, like the on-hold [Why does Stephen Hawking say "Artificial Intelligence will kill us all"?](https://ai.stackexchange.com/questions/7/why-does-stephen-hawking-say-artificial-intelligence-will-kill-us-all).
And this suggests that the AI experts are going to become rapidly bored and leave, since they can't ask the questions they're interested in and don't see any interesting questions to answer, and so they won't be around to contribute to the humanities side of the discussion. What good humanities questions have we had, so far? My short list is something like:
[What is the different between strong-AI and weak-AI?](https://ai.stackexchange.com/questions/74/what-is-the-difference-between-strong-ai-and-weak-ai) (though this is another 101 question)
[Is the Turing Test, or any of its variants, a reliable test of artificial intelligence?](https://ai.stackexchange.com/questions/15/is-the-turing-test-or-any-of-its-variants-a-reliable-test-of-artificial-intell)
[What limits, if any, does the halting problem put on Artificial Intelligence?](https://ai.stackexchange.com/questions/148/what-limits-if-any-does-the-halting-problem-put-on-artificial-intelligence)
But that's three good humanities questions out of the [15 currently most upvoted questions](https://ai.stackexchange.com/questions?sort=votes).
Upvotes: 2 <issue_comment>username_4: Add bounties.
-------------
What else can you do? Adding bounties to questions puts them in a special category on the front page. If you want, you could even have two users who 'bounce' a bounty to each other on few questions, to make sure that they stay there in the 'featured' tab.
Upvotes: 0 <issue_comment>username_5: I'd like to point out that every site has a greatest hits page. Ours is at
<https://ai.stackexchange.com/questions/greatest-hits>
Ours is currently empty, unfortunately, but I suspect that there will be questions there within a month or so. (An older site, Monero, still doesn't have any questions in this list. On the other hand, the Language Learning site does, but that site is already three months old.)
Upvotes: 2 <issue_comment>username_6: Upvote *only* good questions.
Down- and/or close-vote *all* bad questions.
Upvotes: -1
|
2016/08/05
| 862
| 3,333
|
<issue_start>username_0: There is a constant war between spammers and website operators, to prevent websites from spam. CAPTCHA's are the tools to protect sites, and are the front line of this arms race.
This is an area of AI research that is directly relevant to the public.
The question is if we should allow postings about how to defeat CAPTCHA's. They are probably in scope, but we don't want to help spammers.
[Obligatory XKCD link](https://xkcd.com/810/).
We may get some inspiration from Security.SE. They have some experience in dealing with ethical issues. Over there, they have an explicit close reason for questions about hacking other systems:
>
> Questions asking us to break the security of a specific system for you are off-topic unless they demonstrate an understanding of the concepts involved and clearly identify a specific problem.
>
>
>
Maybe we need a similar close reason or off-topic flag?<issue_comment>username_1: (Without seeing any actual examples…)
These can likely be closed as off topic *already.* A question sufficiently detailed enough to ask how to defeat a system based in AI will likely no longer be about the ***subject*** of AI itself. It would be like asking how to defeat the smart aliens in Galactic Uberblast 2020, or how to remove the T47/a access panel of your robot butler if he wont let you.
There's a point where a question is only *coincidentally* related to the subject of AI itself — close it as off topic.
There will always be sticky edge cases where someone might be asking how an AI-based security system **works,** but it becomes somewhat problematic to preempt any such questions by presuming the *intent* of an author before you see such questions in actual practice. It's probably too early to conjure up a broad policy statement when there is really no tangible problem to defeat.
Upvotes: 3 <issue_comment>username_2: Asking about how Captcha works or what is mechanism of AI recognising the text from the image, isn't illegal.
Neither whether has been cracked/hacked or not, which has been asked at Stack Overflow:
* [Has reCaptcha been cracked / hacked / OCR'd / defeated / broken?](https://stackoverflow.com/q/448963/55075)
Captcha is just a type of challenge-response test used in determine whether somebody is human or not and this technology is not owned by anybody. There are many research studies how to improve this technology to keep spammers away.
If the post doesn't indicate it's against the law and doesn't show any illegal activity, there is no reason to close it. If it's unethical, you can always down-vote it or ask for clarification. There are special agencies which deals with that problem, so you don't have to worry about it.
If it's not illegal, it's up to you how you'll use the knowledge from the posts. As it can be always used for research and educational purposes.
See also:
* [Should unethical questions be answered?](https://meta.stackexchange.com/q/21706/191655)
* [Policy regarding questions related to unethical or “shady” practices](https://meta.stackexchange.com/q/80495/191655)
>
> we bury our heads in the sand, we're just pretending the problem doesn't exist and we can't help defend against it
>
>
> If a process is clearly illegal, especially in the US, then it should not be discussed.
>
>
>
Upvotes: 0
|
2016/08/05
| 789
| 3,225
|
<issue_start>username_0: This is my question about a very common problem faced while training several data science and AI algorithms, and most importantly while backpropogating errors in neural networks, which is **getting trapped in a local minima while descending gradient.**
So, according to the discussion under the qn, it is [claimed to be off-topic](https://ai.stackexchange.com/q/1362/101)
However, in the defence of my post, I think it is perfectly on-topic in this site, as it asks about a legit problem faced while training neural nets and several other AI algorithms.
So, I am looking forward to what the community thinks regarding this.<issue_comment>username_1: Escaping local optima is an extremely ubiquitous problem (in case it's unclear - there are vastly more applications than backprop), leading to many open questions (a great deal of metaheuristics research, indisputably part of AI, is concerned with this).
So, it is much more open-ended (and therefore subject to heuristic/AI solutions) than the more pedestrian questions (with procedural anwers) about e.g. backprop that appear to be within the AI SE remit.
Hence, I'd say it is definitely on topic ;-)
Upvotes: 1 <issue_comment>username_2: The question is off-topic, as it's about how to the use of machine learning algorithms. (the other questions on neural nets, their architectures, backpropogation, are also off-topic).
Programming, algorithm, modeling, math, philosophy, and history questions should the off-topic, as they are already on-topic in [other SE](https://ai.meta.stackexchange.com/q/4/4), such as Stats and Data Science.
Data science and the Stats SE already have a huge overlap (>~80%), and I am worried to have a third SE that also significantly overlaps with them. Personally, it would further demotivate me to write any answer, as it gets tiring to copy-paste content, and updating duplicated answers is a pain.
Upvotes: 3 [selected_answer]<issue_comment>username_3: Personally, I consider gradient descent something akin to what something like differential equations is to physics - a useful piece of mathematics that has a large array of applications, but not really an AI topic by itself.
---
When we talk about AI, there are different levels of detail and "technicalness" we can go into and I believe it's necessary to draw the line somewhere.
To illustrate what I mean, let me use the example of self-driving cars:
* There's the concept of the **self-driving car** itself
* The car has some sort of **computer-vision** system
* That system might involve a **neural network**
* That network needs to be **trained** somehow - there are different algorithms for that
* One of the most common ones is **backpropagation**
* Backpropagation often uses **gradient descent**
* Gradient descent is an **optimization algorithm**
* and so on...
We could look at an AI problem at any of those levels. But at some point, it becomes no longer really about AI but rather about mathematics or statistics. And those topics are already covered well by other sites.
Basically, what I believe is that this site should mainly concentrate on the top few lines of that list, and leave the rest to more appropriate venues.
Upvotes: 0
|
2016/08/06
| 1,133
| 4,520
|
<issue_start>username_0: So, can someone help me understand what the scope of the site is?
[I ask a question about Monte Carlo search](https://ai.stackexchange.com/q/1358/101), which is one of the core algorithms behind the Go playing **AI bot**, AlphaGo, and it is closed off as off-topic, citing this reason `This question does not appear to be about artificial intelligence`.
So, my question is: **Why isn't it about AI?** Isn't AlphaGo an AI bot? Why does asking about an AI algorithm of an AI bot make it off-topic?
**Can someone(maybe one of the close-voters) take the example of AlphaGo and explain what an on-topic question and an off-topic question(<-- You can use mine if you want to.) would look like?**
[I already asked a question about the scope of this site](https://ai.meta.stackexchange.com/q/1091/101), citing another example, where I'm yet to get a clear answer.
If all the questions get closed as on-topic in DS and CV, then why do we even have this site? (Sorry if I sound rude, but I really want this site to grow. So, the early we sought out our scope, the better.)<issue_comment>username_1: I was one of the close voters.
First up, the close message you see is the generic off-topic message - we only get one reason under the "off-topic" branch of the close dialogs because we currently have no moderators to create and approve off-topic reasons. Therefore, anything deemed off-topic will get that one message. It's not that your question wasn't about AI, it wasn't about AI *as defined in the help center* (or, again, since we have no moderators yet, as defined on meta).
Your question, in my understanding, is about specific algorithms and how they work. We're not really into the math/statistics/implementation on this site, because those are already well covered by existing places.
I think that the question could be reopened if it was adjusted to ask something like "Why is Alpha Go's approach more appropriate for games than existing technologies?" Then the question wouldn't be about a specific algorithm, but answers could still dive in if they wanted.
As for whether we have a scope, we're still working on that, as evidenced by our abundance of meta posts about topicality! I think we do have at least some sketches of what should by on- and off-topic, though.
Upvotes: 2 <issue_comment>username_2: The initial scope on [Area 51](http://area51.stackexchange.com/proposals/93481/artificial-intelligence) proposal was:
>
> Conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.
>
>
>
Of course this isn't a strict rule, because the final scope is defined by community based on the questions being asked, so if you have any great question related to AI, please ask. So after some time this site can find a distinct and unique scope in comparison to other existing [network sites](http://stackexchange.com/sites#science-questionsperday).
However please note that the questions about [programming](https://stackoverflow.com/), [algorithms](https://ai.meta.stackexchange.com/q/71/8), [implementation](https://stats.stackexchange.com/questions/tagged/machine-learning) and [data modelling](https://datascience.stackexchange.com/questions/tagged/machine-learning) are already on-topic on the other dedicated sites and are likely to be off-topic here in order to avoid [huge overlap](https://ai.meta.stackexchange.com/q/4/8).
---
Basically the scope is still about **artificial intelligence**, but coming from the technical background, asking the right question could be challenging (because we've already a lot of sites dedicated to different aspects of AI). You can think about it like [Programmers](https://softwareengineering.stackexchange.com/) SE site, but without asking actual programming questions.
Upvotes: 1 [selected_answer]<issue_comment>username_3: I don't know, but that shouldn't have been closed. It should be, in almost every case, sufficient to simply *ignore* any question which falls into a "grey area" regarding scope. We should only close questions which are blatant spam, trolling, or so wildly off-topic that a 2 year old could see it (like a question about the best fuel injector cleaner to use for 1972 Ford Pinto, or something).
If questions are desired by the community, they'l bubble to the top. If they aren't, they'll die from lack of activity. Explicitly closing a question is an aggressive and hostile act and should always be a measure of last resort.
Upvotes: 2
|
2016/08/07
| 641
| 2,413
|
<issue_start>username_0: It would be nice to add <https://stats.stackexchange.com/> as a migration target:
[](https://i.stack.imgur.com/emrFr.png)<issue_comment>username_1: Yes, that would definitely be a good idea; we get a lot of questions that belong there.
The trick is that sites only get migration paths (in or out) after they graduate fully. The reasoning behind this is that beta sites are still figuring out their scopes, and it would be bad to send a question away forever with no way to reopen it at the source site.
Moderators can migrate things anywhere, but only if the question is less than 60 days old. If we get pro-tem mods in time, we could consider sending any good-but-definitely-off-topic questions away.
People might also want to migrate to [Data Science](https://datascience.stackexchange.com/), but it's still in public beta and is therefore not guaranteed to stick around. Migrations to beta sites are [discouraged](https://meta.stackexchange.com/a/258601/295684).
Upvotes: 2 <issue_comment>username_2: I think we should have first the list of questions which are off-topic here, and on-topic there. If we've enough number of them, the migration target probably can be added later on. For now you can flag each question for moderation, so it can be migrated manually when accepted.
However as far as I've checked, there are only 73 questions tagged with [artificial-intelligence](https://stats.stackexchange.com/questions/tagged/artificial-intelligence) on Stat.SE where 1/3 of them are still unanswered (24), so I believe some questions about artificial intelligence probably are better suited here. Unless they're specifically related to [machine-learning](https://stats.stackexchange.com/questions/tagged/machine-learning) where, again, 40% of them are unanswered which make us think where they really belong.
On the other hand, using/programming/implementing AI, at the same time doesn't make me expert on statistics aka cross-validation/rotation estimation model, which to be honest, I don't know nothing about.
And it's not only me:
>
> statistical learning is not the path to AI (Artificial Intelligence)
>
>
>
Source: [Quora](https://www.quora.com/I-once-heard-statistical-learning-is-not-the-path-to-AI-Artificial-Intelligence-what-are-the-arguments-that-support-this-statement-claim).
Upvotes: 1
|
2016/08/09
| 1,098
| 4,005
|
<issue_start>username_0: Currently we've the following tags related to gaming:
[ai-games](https://ai.stackexchange.com/questions/tagged/ai-games "show questions tagged 'ai-games'"), [gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'"), [go-game](https://ai.stackexchange.com/questions/tagged/go-game "show questions tagged 'go-game'"), [game-theory](https://ai.stackexchange.com/questions/tagged/game-theory "show questions tagged 'game-theory'"), [game-play](https://ai.stackexchange.com/questions/tagged/game-play "show questions tagged 'game-play'"), [games](https://ai.stackexchange.com/questions/tagged/games "show questions tagged 'games'").
Can we decide on one or two to stick with related to gaming? Which one would be the most suitable?<issue_comment>username_1: I would go with [gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'"). It's implied that questions on an AI site will be about AI, so there's no need to specify that in a tag. The gerund form makes it clear that gaming is something the AIs are doing.
We can add tags for specific games (like Go) if they become big topics.
Upvotes: 2 <issue_comment>username_2: Some of these tags seem related but I think [game-theory](https://ai.stackexchange.com/questions/tagged/game-theory "show questions tagged 'game-theory'") has a well-known definition (from [wikipedia](https://en.wikipedia.org/wiki/Game_theory))
>
> the study of mathematical models of conflict and cooperation between
> intelligent rational decision-makers
>
>
>
and it's applied in other fields besides AI.
IMO there should also be different tags for `AI that's used in games` and `AI that plays games`, the first may correspond to [gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'") [games](https://ai.stackexchange.com/questions/tagged/games "show questions tagged 'games'") or so and I would call the second [game-play](https://ai.stackexchange.com/questions/tagged/game-play "show questions tagged 'game-play'").
Moreover [Go](https://en.wikipedia.org/wiki/Go_(game)) refers to that specific board game, which had for long been considered as the only game that humans play better than machines until the AI [AlphaGo](https://en.wikipedia.org/wiki/AlphaGo) came into play. So [go-game](https://ai.stackexchange.com/questions/tagged/go-game "show questions tagged 'go-game'") seems to be particularly for [Go](https://en.wikipedia.org/wiki/Go_(game)).
So IMO at least [game-theory](https://ai.stackexchange.com/questions/tagged/game-theory "show questions tagged 'game-theory'") [go-game](https://ai.stackexchange.com/questions/tagged/go-game "show questions tagged 'go-game'") have clear definitions, and among the others there should be separate tags for `AI that's used in games` and `AI that plays games`.
Upvotes: 2 <issue_comment>username_3: I think there is a bit of a difference between [games](https://ai.stackexchange.com/questions/tagged/games "show questions tagged 'games'") and [gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'"). I wouldn't call playing Go or chess gaming. I might call it, depending on the context, playing a game.
On the other hand, playing a game such as World of Warcraft or Plants vs. Zombies, I would call gaming. (not that I do it...)
Upvotes: 0 <issue_comment>username_4: I think there should be two tags here:
**[gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'") and [game-theory](https://ai.stackexchange.com/questions/tagged/game-theory "show questions tagged 'game-theory'").**
[gaming](https://ai.stackexchange.com/questions/tagged/gaming "show questions tagged 'gaming'") is for how AIs are used *in games*.
[game-theory](https://ai.stackexchange.com/questions/tagged/game-theory "show questions tagged 'game-theory'") should be used for AIs *playing games*.
Upvotes: 2 [selected_answer]
|
2016/08/10
| 1,002
| 3,931
|
<issue_start>username_0: At the beginning we were worried that this site won't provide anything useful. Is that still the case?
As [@Ben](http://chat.stackexchange.com/transcript/message/31517321#31517321) mentioned:
>
> Right now, the default state is **fail** unless we can show SE that we bring something new to *the* network.
>
>
>
Have we managed to bring something new to the [network](http://stackexchange.com/sites#science-questionsperday) and this site has found its own distinct and unique scope? What do you think and why?
---
Btw. I've already posted my opinion [here](https://ai.meta.stackexchange.com/a/1119/8).<issue_comment>username_1: It's a tricky question.
*This is NOT a site review, but a personal observation having followed this subject on the network for some time.*
I think we've done a better job at scoping out something fundamentally more useful as a site. The formative question is whether we have a suitable audience to actually build out this space. But that has to happen here and now; they won't just *show up* later.
Stack Exchange is billed as a network of practitioners helping their peers solve everyday problems. Unfortunately, a large percentage of the questions being asked here sit squarely in the curiosity-seekers space. Questions mostly wallow conspicuously in played-out subjects which "real" AI researches have stopped asking a long ago — Is *this* AI? What does *concept* mean? When are we going to get there? When is AI going to do {x}?
I won't pass judgement on whether we've given up on actually building a peer-review site. I talked about some of this in [no artificial intelligence in Area 51](https://blog.stackoverflow.com/2010/12/no-artificial-intelligence-in-area-51/).
There are certainly at least a few very knowledgeable people in this community — actual researchers working in this field — but there's a bifurcation of posts from folks with *active* experience and someone just showing up with whatever they find in a cursory Google search. **The problem is that the community either doesn't know the difference, or doesn't care to vote up one over the other.** It's hard to fault anyone for trying valiantly to get something going here, but watching something from Wikipedia being voted on with equal alacrity is somewhat… discouraging.
### Have we brought something new to the network?
Probably. Questions here don't generally fit elsewhere.
### Have we created something useful?
Hard to say; that's a big question for the final review.
### Does this a address a peer group prevalent in this space?
That does not seem likely — If you read [**Asking the First Questions**](https://blog.stackoverflow.com/2010/07/area-51-asking-the-first-questions/), I suspect that ship will have sailed by time we reach public beta.
### Have we improved the Internet in general?
My suspicion is the lack of true peer review in this space will make most of what is posted here about *status quo* with what you can already find elsewhere. That is by no means certain; that is just my observation.
Upvotes: 3 <issue_comment>username_2: *Have we brought something new to the network?*
I think so. Yes, there's overlap with other sites, and yes it would be nice to have more deeper / research level questions and answers. But I posit that getting to that level will happen IF the site is given enough time. That and if we don't chase too many users away with too much bureaucracy and pedantry.
Remember the old ai.se was actually working well, just at a scale that was - at the time - deemed too small by the se powers-that-be. If this site is allowed to live post-beta, I expect it to get steadily better. Keep in mind, AI is difficult because it's such a broad topic. And even now there's lingering resistance among some people to talking about "artificial intelligence" (as opposed to "machine learning", etc.) after the various AI Winters of the past.
Upvotes: 2
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2016/08/10
| 872
| 3,366
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<issue_start>username_0: We've this old thread at Area 51 (related to older site proposal which failed):
* [How is this proposal different from Cross Validated?](https://area51.meta.stackexchange.com/q/11659/61861)
In general accepted [post](https://area51.meta.stackexchange.com/a/11708/61861) says:
>
> First of all, artificial intelligence is a much broader term than machine learning. While at the same time Cross Validated is not about machine learning, but about statistics.
>
>
>
Is it still valid point? Can we elaborate on this further more?
How this site is different from *Cross Validated*? Do we have now more arguments to it?<issue_comment>username_1: I'm of the opinion that we should allow ML and AI research-style questions here, of the sort that would also *could* be on-topic at Cross Validated but would be less likely to hit their intended audience there than they would here.
That is, I don't think there is a difference in topics so much as there is a difference between clusters of people who care about those topics, and the perspectives that they bring and the sort of questions and answers that they'll consider interestingly on-topic.
Upvotes: 2 <issue_comment>username_2: >
> While at the same time Cross Validated is not about machine learning, but about statistics.
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This is not a valid point, as all machine learning questions are on-topic on CV.
It's unclear to me what extent non-statistical AI is on-topic on CV, so I asked there <https://stats.meta.stackexchange.com/questions/4257/what-is-our-stance-on-questions-about-non-statistical-artificial-intelligence> If no, it makes sense to have a (non-stat?) AI site. If yes, I think we should merge and rename CV.
Upvotes: -1 <issue_comment>username_3: Clearly, [Cross Validated](https://stats.stackexchange.com/) is about statistics - it's even in the URL, `stats.stackexchange.com`. They're a very math-heavy and calculation-oriented site. MathJax is enabled there, and every question I scanned from their front page involves code or mathematical formulae. [machine-learning](https://ai.stackexchange.com/questions/tagged/machine-learning "show questions tagged 'machine-learning'") is their third most popular tag at the moment, and [questions in it](https://stats.stackexchange.com/questions/tagged/machine-learning) are about the stats/math involved in machine learning.
Questions here are not expected to involve that level of detail. MathJax is not enabled here, and that [might](https://ai.meta.stackexchange.com/q/35/75) be purposeful. Our questions should be about the [science](https://area51.meta.stackexchange.com/a/24016/136466) - not so much the technology or math or implementation of - artificial intelligence. (For machine learning implementation, see [Data Science](https://datascience.stackexchange.com/).)
Upvotes: 3 [selected_answer]<issue_comment>username_4: AI is broader than Machine Learning and Statistical Learning. Yes, the probabilistic / statistical stuff dominates the conversation these days, but AI includes rule based systems, expert systems, symbolic processing, logic programming and other things that would not be on-topic at Cross Validated (or Data Science).
We've also been saying that we have more of a focus on the philosophy of AI and the humanities related aspects, as opposed to strictly the technology.
Upvotes: 2
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2016/08/11
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<issue_start>username_0: By AI programming, I mean somebody asks how to solve programming issue which deals with AI logic specifically, e.g.
* [Why does my NN not classify these tic tac toe pattern correctly?](https://ai.stackexchange.com/q/1570/8)
The above example uses Keras, highly modular neural networks library written in Python.
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Are these off-topic and why they cannot be here?
If not, would be this ever considered? Especially the code which is very specific to AI coding?
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Related: [What kind of experts are we trying to attract?](https://ai.meta.stackexchange.com/a/46/8)
>
> In fact, I think now that implementation questions would benefit from a dedicated site (my view has evolved since the Area 51 definition phase). I have replied and tried to reply to several SO questions related to ML tools, and I think some are out of place compared to other questions. For example, some TensorFlow questions are not really programming questions, and not really framework questions. I mean, there is background knowledge on graph construction and execution, as well as background knowledge about statistics and probabilities that are really necessary to make meaningful contributions.
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> This is not to say that all questions are out of place on SO. Some are really framework issues or (Python) programming issues, and they are good there.
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> Based on this opinion, I think the site should be interested in implementation experts, whether they work on ML or Expert Systems (or both?).
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> -- @EricPlaton
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>
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So we're talking about coding highly modular neural networks libraries which require advanced background knowledge and AI expertise, and it was suggested.
The same as other specific modular frameworks, where coding questions are on-topic on their dedicated websites, they're allowed on: [Drupal.SE](https://drupal.stackexchange.com/), [Wordpress.SE](https://wordpress.stackexchange.com/), [TeX.SE](https://tex.stackexchange.com/), [Apex at Salesforce.SE](https://salesforce.stackexchange.com/questions/tagged/apex), etc. For a standard programmer without specific expertise, these are a bit of out-of-place on Stack Overflow.<issue_comment>username_1: In general, I think that we should allow questions on neural network architecture in order to attract and retain experts who actually build state of the art systems.
But for that specific question, I'm torn and lean towards keeping it closed. It's a novice instead of an expert architecture question; a good answer to it looks more like an explanation of how the necessary number of training examples scales with rule complexity, and how to ensure that the model depth and breadth is sufficient to encode rules of a certain complexity, and maybe also how to 'cheat' on model size and training requirements with convolution layers.
But if we want a question to expound on that sort of 101 material, it should probably be a set of three specific, easily searchable questions rather than the question that actually exists.
Upvotes: 3 [selected_answer]<issue_comment>username_2: There are already plenty of questions on programming AI/NN frameworks on Data science and SO: I don't think we need one more place, SE is fragmented enough.
Upvotes: -1 <issue_comment>username_3: Our site was created to hold questions about the scientific and social - not technical or programmatical - aspects of artificial intelligence. That's evidenced by its original section in Area 51, and by several posts by Stack Exchange staff. For example, see [this answer](https://ai.meta.stackexchange.com/a/1199/75) on the question about summarizing our scope (relevant part reproduced here):
The proposal that created this site was intentionally placed in the 'scientific' category. If you accept that we are not creating another programming site, I think we stumbled upon in interesting niche that describes the original premise of this site nicely:
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> >
> > Artificial Intelligence Stack Exchange is a site with a social and scientific focus on "Advanced Computing in Society."
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> >
> >
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> Think about it. With autonomous cars, smart surveillance, and "the next big thing" capturing the headlines, this isn't a terrible idea for a subject. Draping it in the popular AI label gives it a better focus… and it completely disambiguate [sic] that **this is *not* a technical implementation or programming site.** We already have that.
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The emphasis was in the original.
Especially when we actually have a pretty cool scope draft (as summarized there), I don't think we should add an extra place in the network for AI-related programming questions.
Upvotes: 0 <issue_comment>username_4: As far as I'm concerned, programming questions should be on-topic IF they are highly specific to AI. That is, if somebody asks "How do I add an item to a collection in Java", that would be off-topic even if they were building an AI application. But if somebody is doing something very specialized like Answer Set Programming in Prolog, etc., then I think this community would be best suited to answer that and, as such, the question should be considered on-topic.
Upvotes: 2
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2016/08/12
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<issue_start>username_0: You can see that [here](http://area51.stackexchange.com/proposals/93481?phase=commitment). However, most of the questions here feel rather more on the technological side of artificial intelligence. Those questions are on-topic on Data Science. *That* site was created as a site for the technological aspect of machine learning and AI, and *that* is the site that is in the Technology category (see [here](http://area51.stackexchange.com/proposals/55053?phase=beta)), in spite of having "Science" in its name.
This was already emphasized by <NAME> on [Area 51](https://area51.meta.stackexchange.com/questions/24014/will-machine-learning-be-considered-as-on-topic):
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> Data Science is an *applied* site for all the programmers/statisticians/mathematicians who are trying to make this stuff *work*. [...]
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> Notice that this proposal is in the 'Science' category; *not* 'Technology'. [...]
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> It was convincing enough to give this site another try, but if this site were to simply start reiterating the implementation/tools questions that are already covered elsewhere, this site will not likely make it out of private beta.
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I already tried to give a hint where we could find science questions here:
[Where can we find the science part of Artificial Intelligence?](https://ai.meta.stackexchange.com/questions/1126/where-can-we-find-the-science-part-of-artificial-intelligence) That is one thing we could do: ask more science questions. The other thing we can do, is closing questions. *Please do close* questions that are highly technological or asking for applications.
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I'd like to link some questions that are, in my opinion (but I could be wrong), scientifical :
* [How is it possible that deep neural networks are so easily fooled?](https://ai.stackexchange.com/questions/92/how-is-it-possible-that-deep-neural-networks-are-so-easily-fooled)
* [What is the difference between strong-AI and weak-AI?](https://ai.stackexchange.com/questions/74/what-is-the-difference-between-strong-ai-and-weak-ai)
* [What limits, if any, does the halting problem put on Artificial Intelligence?](https://ai.stackexchange.com/questions/148/what-limits-if-any-does-the-halting-problem-put-on-artificial-intelligence)
* [Are there any AI that have passed the MIST test so far?](https://ai.stackexchange.com/questions/1397/are-there-any-ai-that-have-passed-the-mist-test-so-far)
* [Has the Lovelace Test 2.0 been successfully used in an academic setting?](https://ai.stackexchange.com/questions/1451/has-the-lovelace-test-2-0-been-successfully-used-in-an-academic-setting)
* [Does the Chinese Room argument hold against AI?](https://ai.stackexchange.com/questions/123/does-the-chinese-room-argument-hold-against-ai)
* [Do scientists know what is happening inside artificial neural networks?](https://ai.stackexchange.com/questions/1479/do-scientists-know-what-is-happening-inside-artificial-neural-networks)
* [Could a Boltzmann machine store more patterns than a Hopfield net?](https://ai.stackexchange.com/questions/1525/could-a-boltzmann-machine-store-more-patterns-than-a-hopfield-net)
There are more questions around that are scientifical and high-quality (fortunately), I just picked a few from the first page of the highest voted list.<issue_comment>username_1: Also a friendly reminder that our [tour page](https://ai.stackexchange.com/tour) (also [proposal](http://area51.stackexchange.com/proposals/93481/artificial-intelligence)) states:
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> A question and answer site for people interested in **conceptual questions about life and challenges in a world** where "cognitive" functions can be mimicked in purely digital environment. It's built and run by you.
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So I don't see the reason why both kind of questions can be on-topic, conceptual and scientific or similar, otherwise we're limiting without any good reason.
Also please remember that it's run by us, so everybody can decide whether question should be on-topic by voting on it.
Upvotes: 0 <issue_comment>username_2: I've seen this argument come up [here](https://ai.meta.stackexchange.com/a/1142/95) and several times in other discussions about scope:
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> I don't see why both kinds of questions can't be on-topic
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It's because the OPPOSITION against creating this site argued (correctly) that we already created sites to handle this subject explicitly. The argument FOR creating this site claimed that we have a missing socio-scientific angle that needed filling.
**Private beta tests if that is a valid premise for creating a NEW site.**
If the founding community does not live up to those expectations, it creates a strong argument for "I told you so" — that the initiative has failed.
**Stick to the mission.**
Don't give credence to arguments for closure.
Upvotes: 4 [selected_answer]<issue_comment>username_3: >
> Data Science is an applied site
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Yeah, for *data science*. Data science is not artificial intelligence. There is overlap around the statistical techniques for machine learning, but they just are not identical.
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> Please do close questions that are highly technological or asking for applications.
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I'm sorry, but I think this is very misguided. Ignoring all aspects of implementation and technology on a se like this, is like a football team fielding an offense, but no defense (or vice versa). Or maybe I should say, it's like a Reese's Peanut Butter Cup without the chocolate.
The simple truth is, you can say "programming questions belong on xx.se (or so)" but there are programming questions which - in principle - would be best suited for this site. If somebody is asking about an AI specific technique or something highly specialized like rule induction using OPS5, this community is probably a better resource than datascience.se, stats.se, or possibly even so.
Upvotes: 3
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