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Gender
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2 values
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transcript
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1
1
S
4
3.8
4.2
1,395
Female
Train
is going to be very difficult moving forward even in a... i don't know-
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S
4.2
4.6
4.6
1,395
Female
Train
... post vaccine environment with so many all you can eat buffets down for the count or otherwise closed across waterloo region.
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H
4.6
5
5
1,395
Female
Train
always did look forward to going to the university club at thanksgiving and at christmas time, and i hope that it makes a return under safer circumstances in the-
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S
3.8
2.8
3.8
1,395
Female
Train
honestly, i never ever was comfortable with buffets ever.
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X
5
5
4.6
1,395
Female
Train
well, i checked in with the good people who run the annual university christmas project and this year all 200 children from working poor families who'd been identified as needing-
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H
4.4
5
4.2
1,395
Female
Train
indeed, for those of you sponsoring a child this year-
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H
4.8
4.8
4.6
1,395
Female
Train
the organizers want to thank the university supports amazing support for families in waterloo region-
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N
4
4.6
4
1,395
Female
Train
... particularly during a year when there is just so much need in our community.
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H
4.6
4.6
4.8
1,395
Female
Train
the agreements which are in effect from 2020 to 2025-
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H
4.6
5.4
4.6
1,393
Female
Train
... introduced a new performance based funding model, including metrics on student and economic outcomes.
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N
4.2
3.8
4
1,393
Female
Train
a delay which has resulted from the covid19 pandemic. universities are not measured against other institutions, but-
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X
4.2
5.2
4.6
1,395
Female
Train
can still provide feedback on the proposed revisions to the policy via email until december 18th.
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N
5
4.6
5
1,395
Female
Train
the pandemic, and what excites him about the future of mathematics.
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H
4.4
5.2
4.8
1,395
Female
Train
really, this has been an interesting time. as you know i was director of computer science.
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X
3.8
3.2
3.8
1,395
Female
Train
well, we've all gone online now-
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N
4.6
4.4
4.6
1,395
Female
Train
we do have a very large program. we rely on-
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X
4.6
4.6
4.4
1,395
Female
Train
... [inaudible 00:07:48] intimate classes where we have a lot of interaction between faculty and students. and it was at the end of term, which means we had to get very quickly ready-
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H
5
4.4
4.4
1,395
Female
Train
... for what for us is an extremely busy spring term.
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U
4.6
4.8
4.8
1,395
Female
Train
so unlike most universities across the country-
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H
5.2
4.8
4.8
1,395
Female
Train
... and i think we're probably the largest at the university of waterloo.
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N
4.4
4.6
4.8
1,395
Female
Train
the spring terms are very large and very active. math rose is the-
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N
5
4.6
4.6
1,393
Female
Train
... challenge. i mean the enormous and immediate challenge we delivered-
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N
4.6
3.4
4
1,395
Female
Train
... i'll claim it was very good and i think it-
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O
5
3.2
4.4
1,395
Female
Train
... i always think, "well, what are we going to come out with?"
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C
4.8
3.2
5.2
1,395
Female
Train
we operated in the past as perfect, but the professor in front of especially the large class, may not be the perfect mechanism.
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N
5.2
3.2
4.4
1,395
Female
Train
we've learned what hybrid delivery looks like.
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N
4.4
4.4
4
1,393
Female
Train
we've learned how to use online components in our courses.
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N
3.4
4
4.4
1,393
Female
Train
we've learned what modes of interactions will work-
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N
5
4
5
1,393
Female
Train
... and that's an important positive in our response.
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O
4.2
5
4.4
1,393
Female
Train
this should inform things like the lifelong learning initiative that the university is embarking on.
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O
5
3.4
5.2
1,393
Female
Train
it should inform things like our already well developed-
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X
5.2
4.2
4.4
1,393
Female
Train
i think what the students have been coping with and faculty have been coping with is suddenly-
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X
5.4
3.6
5
1,393
Female
Train
... and they're doing a full load and they're thinking about a program.
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X
4.8
3.6
4.6
1,395
Female
Train
i'm not just talking about reducing class sizes or putting everything online.
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X
5.2
3.4
5.2
1,395
Female
Train
i think structure is the structure to an entire program.
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X
4.2
4.4
4.4
1,395
Female
Train
the research on the... or even more, the going to a seminar, because you heard about this-
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X
5.2
3.4
5
1,395
Female
Train
... club or something like that. that has been largely lost as-
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X
4.8
4.2
4.2
1,395
Female
Train
that's certainly been subdued over the past year.
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O
5
2.8
5.2
1,395
Female
Train
and i think that's a serious concern both for our academic health,
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N
4.8
4.4
4.8
1,395
Female
Train
the students especially, but also the faculty and staff at the university.
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O
4.4
4.2
5.2
1,395
Female
Train
these are challenges that universities around the world are facing.
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H
5.2
4.4
5.2
1,395
Female
Train
the faculty of math on all fronts has been doing extremely well.
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N
5.2
4.4
5.2
1,395
Female
Train
on a crude level this speaks very well to the quality of the research of the education we deliver in mathematics.
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N
4
3.4
4.2
1,798
Male
Development
it's not as waterloo defines it to include computer sciences,
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X
5.2
4.4
4.4
1,798
Male
Development
statistics, but in the more traditional field, we're in the top 50 in the world.
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H
5.2
4.8
4
1,798
Male
Development
i think another piece that is,
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S
4.2
3.6
3.6
1,798
Male
Development
another ranking maybe more focused on canadians.
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X
4.4
4.8
5.2
1,395
Female
Train
and i think this speaks to our research and i also think it speaks to our educational delivery to the programs that we deliver, because it's an incredibly powerful,
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N
4.8
4.6
4.6
1,798
Male
Development
set of programs. it speaks to a connection between computer science and statistics.
[ { "feats": [ 0.16956989467144012, -0.1905355006456375, 0.16666652262210846, 0.02784043364226818, 0.6643887758255005, 0.3578563332557678, 0.0790756344795227, 1.0798009634017944, 0.8075618147850037, 0.028643518686294556, -0.8070393204689026, ...
N
4
4.6
4.2
1,798
Male
Development
and i think it means that our student,
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N
4.2
4
4.8
1,395
Female
Train
the students that graduate are extremely well prepared to deal,
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H
5.2
5.4
5.4
1,395
Female
Train
yeah. so that's something that i guess i've been thinking a lot of as i moved from being,
[ { "feats": [ 0.11385977268218994, -0.1983572393655777, 0.22651900351047516, -0.06316249072551727, 0.7365431785583496, 0.4377298653125763, 0.02509673498570919, 1.2630985975265503, 0.734618067741394, -0.031396787613630295, -0.7247905135154724, ...
N
4.6
4.6
4.6
1,798
Male
Development
i'll say a mathematical computer scientist to being,
[ { "feats": [ 0.12064908444881439, -0.27069658041000366, 0.14401815831661224, 0.04574277624487877, 0.6138097643852234, 0.3391020596027374, 0.12019459903240204, 0.9965542554855347, 0.7730085849761963, 0.029035836458206177, -0.8277353644371033, ...
H
5.2
4.4
5.2
1,798
Male
Development
because it's not something i might have been able to speak to quite as,
[ { "feats": [ 0.13298554718494415, -0.15978281199932098, 0.14982999861240387, -0.12950068712234497, 0.8620645403862, 0.48816418647766113, 0.0840788260102272, 1.3526201248168945, 0.8308234214782715, -0.06396275013685226, -0.8131846189498901, ...
O
4.2
4.4
4.8
1,798
Male
Development
obviously 10, 15 years ago. i think the fields have converged in a way that makes me personally very happy. but,
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H
4.4
4.4
3.8
1,798
Male
Development
i think it's very much aligning these areas.
[ { "feats": [ 0.04637438431382179, -0.0685003250837326, 0.24952100217342377, -0.11486395448446274, 0.7136425375938416, 0.3583005368709564, 0.09114062041044235, 1.2120863199234009, 0.692661702632904, 0.059871673583984375, -0.6591905355453491, ...
X
4.2
3.8
4.6
1,798
Male
Development
things like ai, machine learning and data science,
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A
4.6
3.2
4.8
1,798
Male
Development
past 10, 15 years, not to mention the previous 20.
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C
5.4
3.2
5.4
1,798
Male
Development
and the researchers very much in all those departments, there could be people who are in the other department,
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N
4.6
3.6
4.8
1,395
Female
Train
and so talking to each other, and if anything,
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X
5.2
4.2
5.6
1,798
Male
Development
i would like to do is to try to make that a tighter and more natural connection and not something that's just artificial because of some [inaudible 00:02:23],
[ { "feats": [ 0.1671944558620453, -0.1758314073085785, 0.18359044194221497, -0.09009050577878952, 0.7159512639045715, 0.4640311598777771, 0.10342702269554138, 1.2715965509414673, 0.7733116149902344, 0.022403232753276825, -0.8169029355049133, ...
H
4
4.6
4.4
1,798
Male
Development
i think it's something that really is in the air right now.
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A
4.6
2.8
5.4
1,798
Male
Development
it affects the work that i'm doing.
[ { "feats": [ 0.04846641793847084, -0.23586030304431915, 0.19266879558563232, -0.005304856691509485, 0.8340900540351868, 0.355643630027771, 0.15195535123348236, 1.2728599309921265, 0.7533736824989319, -0.052104849368333817, -0.7735162377357483, ...
O
4.6
4.4
4
1,798
Male
Development
it is important that we are co-located or continuously located.
[ { "feats": [ 0.053547680377960205, -0.17977659404277802, 0.20129115879535675, -0.08482905477285385, 0.693088948726654, 0.37589365243911743, 0.09779569506645203, 1.213058590888977, 0.5867092609405518, 0.03859994187951088, -0.7865891456604004, ...
O
4.2
4.2
4.2
1,798
Male
Development
one of the things that i'm working towards in our planning going forward, is that we are very deeply connected and that the pathways are there.
[ { "feats": [ 0.06760205328464508, -0.23348776996135712, 0.22228726744651794, 0.056302089244127274, 0.7056199312210083, 0.42053458094596863, 0.13416357338428497, 1.1711726188659668, 0.648583710193634, 0.0365229956805706, -0.7971935868263245, ...
H
4.8
4.8
4.8
1,395
Female
Train
those connections are there. you might as well encourage them,
[ { "feats": [ 0.048683762550354004, -0.21667803823947906, 0.25683265924453735, -0.11218073219060898, 0.7896177172660828, 0.2738036811351776, 0.028351910412311554, 1.4155607223510742, 0.9167561531066895, -0.005744437221437693, -0.5925476551055908, ...
N
4.6
3.8
4.8
1,798
Male
Development
like with environment or art.
[ { "feats": [ 0.05318450182676315, -0.13537178933620453, 0.3228585422039032, 0.01391975674778223, 0.993170440196991, 0.36021021008491516, 0.031017087399959564, 1.339866280555725, 0.9213206768035889, -0.02147345244884491, -0.9032073616981506, ...
U
4.6
5.2
4.8
1,798
Male
Development
in applied math we have people in statistics who are doing biostatistics and statistical modeling of,
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X
4.8
4.4
4.4
1,798
Male
Development
are very relevant to covid research,
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X
4.8
3.8
4.6
1,798
Male
Development
we'll find members of the school of computer science, applied mathematics and statistics all prominent from waterloo,
[ { "feats": [ 0.1645769625902176, -0.20004437863826752, 0.24427078664302826, -0.046879835426807404, 0.7480919361114502, 0.3302454650402069, 0.0796198919415474, 1.0763527154922485, 0.8795199990272522, -0.020603150129318237, -0.8533883094787598, ...
H
4.6
4.8
5
1,798
Male
Development
was informing our discussions and making advances that will hopefully bring this all to an end.
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N
4.4
4.6
4.2
1,798
Male
Development
connections with arts. i mean everything we do it seems that,
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O
4.4
4.6
5
1,798
Male
Development
and yet most of us are not computer scientists, and we interact with machines socially,
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X
5
3.4
5
1,395
Female
Train
through all things which we're now relying on, whether we're technically adept or not.
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A
3.8
3.4
4.8
1,798
Male
Development
we're now relying on every day in our social interactions.
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O
4.8
4.6
5.2
1,798
Male
Development
what is going on in math that excites you the most?
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H
5
4.8
5
1,798
Male
Development
yeah, i guess one of the things that excites me is the connections between the fields,
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H
4.4
5
4.2
1,798
Male
Development
pieces. that one really excites me.
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N
3.2
3.6
3.4
1,395
Female
Train
i think work in computer security and privacy.
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X
4.4
4.6
4.2
1,798
Male
Development
this is work where the best work is being done in the university.
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X
4.8
4.2
4.4
1,798
Male
Development
but let me talk a little bit about maybe data being the broad theme here, and the ability of mathematics,
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H
4.8
4.2
4.6
1,798
Male
Development
i'll say the defining entity in our society for the last 20 years, if not longer.
[ { "feats": [ 0.043870121240615845, -0.0881836861371994, 0.18485109508037567, 0.019907603040337563, 0.7282456755638123, 0.41230928897857666, 0.08286868780851364, 1.2478801012039185, 0.8180901408195496, 0.013949575833976269, -0.8022902011871338, ...
N
4.4
4.4
4.6
1,798
Male
Development
and i think the place in the academy and probably in society that is best suited to do this.
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N
5.2
4.6
5
1,798
Male
Development
is a faculty of mathematics, one that includes statistics and computer science, because it has the tools. so it also, when i look to the...
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H
4.6
4.6
4.6
1,395
Female
Train
and i know that one of the advantages of being a director of computer science and being a unit head in math for so many years.
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S
4.6
3.2
4.6
1,798
Male
Development
and so that was something important for me to find.
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X
5
3.6
5.2
1,798
Male
Development
and i also think it was something that if we're moving forward and we look to these common themes to build on,
[ { "feats": [ 0.13361856341362, -0.2162388116121292, 0.13832126557826996, -0.022605005651712418, 0.6687591075897217, 0.33745500445365906, 0.0379977785050869, 1.156924843788147, 0.6524515151977539, -0.002689616521820426, -0.7366294860839844, ...
X
4.8
4.8
4.4
1,798
Male
Development
we've been searching them out as we go forward with the mathematics strategic plan,
[ { "feats": [ 0.1025821641087532, -0.19006063044071198, 0.08243773877620697, 0.016012826934456825, 0.6525046229362488, 0.26192888617515564, 0.053537897765636444, 1.08614182472229, 0.7423473000526428, -0.007024432998150587, -0.8327993750572205, ...
X
5.2
4
4.8
1,798
Male
Development
at a data science institute, which will define how,
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N
4.6
4.8
4.8
1,395
Female
Train
it will give a cross sectional view of data across the university and allow us to interact,
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N
5.4
4.6
5.6
1,395
Female
Train
across these artificial barriers that we build up in the university.
[ { "feats": [ 0.14003705978393555, -0.17868535220623016, 0.12502138316631317, -0.02054443210363388, 0.6547205448150635, 0.22091138362884521, 0.02784174121916294, 1.1425721645355225, 0.831836462020874, 0.0812072604894638, -0.7020388841629028, ...
X
5.6
4
4.2
1,798
Male
Development
so there's a plan at the institutional level called the digital futures strategy.
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O
5
3.4
4.8
1,798
Male
Development
and within that is the data science institute that i certainly am crossing my fingers that we,
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O
4.4
5
4.6
1,395
Female
Train
can go forward with in the near future.
[ { "feats": [ -0.0044150641188025475, -0.277609646320343, 0.18486490845680237, -0.004192776046693325, 0.6494461894035339, 0.24183030426502228, 0.07002372294664383, 1.169710397720337, 0.7326048612594604, -0.05477697029709816, -0.7137909531593323, ...
H
4.4
5
4.4
1,395
Female
Train
it's a very effective umbrella to allow for communication on things like,
[ { "feats": [ 0.1017034724354744, -0.14282701909542084, 0.14728717505931854, -0.09715097397565842, 0.778504490852356, 0.43077585101127625, 0.051161982119083405, 1.1617954969406128, 0.7636820673942566, -0.027983924373984337, -0.7886247038841248, ...
N
4.6
4.2
4.6
1,393
Female
Train
.. another piece of this is,
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N
4
4
4.6
1,393
Female
Train
being a research program. research is something where we work with colleagues and we work with colleagues that we're approximate to that we can interact with,
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X
3.6
4.8
4
1,393
Female
Train
all over the world, and waterloo brings those people together under one roof.
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O
5
3.6
5.6
1,393
Female
Train
at an institute, where would that even be?
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S
4.4
4.4
4.6
1,393
Female
Train
and honestly, when it came to the entrepreneurial space, which,
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