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	<div class="doc-header">
	<div class="overline">Primordial Calculus / HIR × OAM — v1.0 OSF Package \| Application Inventory</div>
	<h1>Medical, Health & Human-Services<br>Applications Inventory</h1>
	<div class="subtitle">A comprehensive, bounded, confidence-graded mapping</div>
	<div class="meta">Framework authored by Collin D. Weber · Inventory analysis generated May 2025<br>
	65 application areas · 16 major groups · Honest confidence grading throughout</div>
	</div>

	<div class="framework-summary">
	<h3>Framework Summary — What Is Being Mapped</h3>
	<p>
	<strong>Primordial Calculus</strong> is a formal framework in two interlocking parts: the <strong>HIR model</strong> (Honesty, Integrity, Respect as constructive bedrock) and the <strong>OAM</strong> (Outsourced Agency Model — a degradation/fault model). Both are mathematically structured and carry a 300-year simulation record.
	</p>
	<p>
	<strong>HIR core sequence:</strong> H + I → Fidelity (F) · R + I → Cohesion (C) · F + C → Resonance (Rn). The model is regenerative and non-brittle: weakening one term stresses the system but remaining terms retain corrective pull. A dense HIR core sets local coherence conditions for the surrounding field.
	</p>
	<p>
	<strong>Key developmental variable:</strong> Earned Grit (G = g(P, Rc, t)) — density formed under recursive contact with realism and pressure. Pressure alone does not guarantee maturation; realism is required.
	</p>
	<p>
	<strong>Alchemical Continuity (Ac[t]):</strong> the human capacity to convert pain, memory, grit, and experience into self-owned meaning. Its depletion feeds social harm (N), ecological strain (E), and accumulated degradation (D) in the OAM.
	</p>
	<div class="eq-block">
	HIR Constructive Sequence: F = f(H,I) · C = f(R,I) · Rn = f(F,C)<br>
	Recursive reinforcement: Rn[t+1] = Rn[t] + α(F[t]·C[t]) − δ<br>
	OAM Social Harm: N[t+1] = N[t] + (((b·R·K·P[t]) + (g·R·K·I))·G[t]) + (c·W[t]) + (d·T[t]) + (ha·(1−Ac[t]))<br>
	OAM Degradation: D[t+1] = D[t] + (a·R·K·I·P[t]·N[t]·E[t]) + (rw·Wc[t]) + (sa·(1−Ac[t]))
	</div>
	<p>
	<strong>Scale Invariance (Axiom 6)</strong> is the property that makes multi-domain application analysis honest: the framework is explicitly designed to remain structurally valid across scales and domains. This does not mean all mappings are equally strong — it means the formal architecture is not inherently domain-locked.
	</p>
	</div>

	<div class="boundary-box">
	<strong>Honest Limits of This Inventory:</strong> This framework makes no biological mechanism claims. Its core variables are relational and behavioral, not biochemical or physiological. Mappings at the biological level are structural/analogical unless the domain is explicitly behavioral or systemic. No application in this inventory constitutes a treatment, cure, or validated clinical tool. The framework is pre-validation. Confidence labels reflect structural fit, not empirical validation status.
	</div>

	<p style="color:var(--ink-muted); font-size:14px; margin-bottom:28px;">
	<strong>Contents:</strong>
	</p>
	<div class="toc-grid">
	<span>Group 1 — Medicine / Clinical Support <span class="count-badge">5</span></span>
	<span>Group 2 — Mental Health / Psychiatry <span class="count-badge">5</span></span>
	<span>Group 3 — Rehabilitation / Recovery <span class="count-badge">4</span></span>
	<span>Group 4 — Pediatrics / Child Development <span class="count-badge">4</span></span>
	<span>Group 5 — Palliative / Hospice / End-of-Life <span class="count-badge">4</span></span>
	<span>Group 6 — Addiction / Substance-Use Recovery <span class="count-badge">4</span></span>
	<span>Group 7 — Genomics / Uncertainty Modeling <span class="count-badge">3</span></span>
	<span>Group 8 — Neurology / Brain / Cognition <span class="count-badge">4</span></span>
	<span>Group 9 — Physiological Regulation / Biofeedback <span class="count-badge">3</span></span>
	<span>Group 10 — Infectious Disease / Post-Viral <span class="count-badge">4</span></span>
	<span>Group 11 — Oncology / Cancer <span class="count-badge">4</span></span>
	<span>Group 12 — Disability / Chronic Illness <span class="count-badge">4</span></span>
	<span>Group 13 — Homelessness / Dignity / Community Care <span class="count-badge">4</span></span>
	<span>Group 14 — Public Health / Systems Pressure <span class="count-badge">5</span></span>
	<span>Group 15 — Caregiver / Family Support <span class="count-badge">4</span></span>
	<span>Group 16 — Health Systems Architecture / Triage <span class="count-badge">4</span></span>
	</div>

	<!-- ═══════════════════════════════ GROUP 1 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 01</span>
	<h2>Medicine / Clinical Support</h2>
	<p>Structural mappings to clinical relationship quality, care coherence, ethical boundaries, and moral injury in clinical practice.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">1.1</span>
	<span class="app-name">Therapeutic Alliance and Clinician–Patient Relationship Quality</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR triad maps structurally and directly to the recognized elements of therapeutic alliance. Honesty anchors diagnostic and prognostic transparency; Integrity aligns with clinician consistency, role coherence, and follow-through; Respect anchors dignity, non-destruction of the patient's self-concept, and relational safety. Fidelity (H+I) maps to trustworthiness in the clinical encounter; Cohesion (R+I) maps to relational stability and continuity of care. The regenerative, non-brittle architecture matches the clinical reality that therapeutic ruptures can be repaired rather than being irreversible. The baseline-setting property maps to how a highly coherent clinician can stabilize a dysregulated patient through steady presence.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Care-process · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR variables (H, I, R, F, C, Rn) are structurally isomorphic with established therapeutic alliance components (trust, consistency, respect, bond, task agreement). The baseline-setting property maps to clinician-as-stabilizer literature.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The framework has not been operationalized into clinical alliance measurement instruments. Direct empirical comparison with validated alliance scales (WAI, RTAS) has not been performed.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">1.2</span>
	<span class="app-name">Clinical Team Coherence and Interprofessional Care Coordination</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR framework maps to interprofessional team dynamics. Team fidelity (H+I) maps to shared diagnostic honesty and role consistency; team cohesion (R+I) maps to respectful coordination across disciplines. The compounding degradation dynamics in OAM (R×K×I — ideological saturation, compliance rigidity, institutional penetration) model how bureaucratic health systems erode collaborative judgment over time. The non-brittle architecture suggests that partial breakdown of team communication does not necessarily collapse care quality if remaining coherent members exert corrective pull.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM variables (K, I, M — compliance rigidity, institutional penetration, coercive enforcement) directly model the dynamics that degrade interdisciplinary team function.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Team science has its own validated frameworks (TeamSTEPPS, IOM models). The PC framework would need to demonstrate distinct predictive value.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">1.3</span>
	<span class="app-name">Informed Consent Quality and Patient Decisional Agency</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR Honesty variable maps directly to the quality of clinical information disclosure — whether clinicians provide honest prognosis, risk disclosure, and option framing. OAM's Institutional Penetration (I) and Compliance Rigidity (K) model how institutional pressures degrade the honesty of informed consent processes. Agency Erosion in OAM maps to the documented phenomenon of patient agency displacement by clinician decision authority. The non-degrading Ac variable (alchemical continuity) maps to the patient's maintained capacity to integrate information and make self-owned decisions.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Care-process · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM agency erosion variables (q, G[t], N[t]) structurally model how institutional systems can displace patient decisional authority.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Consent law and ethics frameworks are well-established. The PC framework's contribution here would be additive framing, not a replacement for existing bioethics structures.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">1.4</span>
	<span class="app-name">Healthcare Worker Moral Injury</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Moral injury in healthcare — the damage from acting against one's values under institutional pressure — maps directly to HIR depletion driven by OAM variables. A clinician with high HIR core density (strong personal fidelity, cohesion, resonance) enters a system with high compliance rigidity (K), institutional penetration (I), and coercive enforcement (M). The recursive degradation model captures how these OAM pressures chronically undermine H, I, R → F, C, and ultimately Rn in the clinician. The Ac depletion pathway (loss of meaning-conversion capacity) maps precisely to the described phenomenology of moral injury. The regenerative reclamation property maps to known resilience factors in moral injury recovery.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Behavioral · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Both HIR depletion under OAM load and moral injury describe the same dynamic: high-integrity agents whose core relational values are structurally overridden by institutional pressure. Ac maps directly to the meaning-making capacity that moral injury damages.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Moral injury has well-established clinical definitions (Shay, Litz). The PC framework's operationalization would need translation into measurable clinical variables to move beyond conceptual mapping.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">1.5</span>
	<span class="app-name">Ethical Boundary Maintenance in Clinical Practice</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The Respect variable's formal definition — "regard for dignity, boundaries, consequence, and shared life" — directly anchors the ethical boundary concepts central to clinical practice guidelines. The OAM Compliance Rigidity (K) and Coercive Enforcement (M) variables model how institutional pressures can force clinicians to override ethical judgment. The HIR baseline-setting property maps to the documented phenomenon of ethical climate contagion in clinical units, where highly principled senior clinicians establish norms that protect ethical practice across the team.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Care-process · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The Respect variable's formal definition is unusually precise about boundary and dignity language, with direct clinical ethics relevance.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Clinical ethics has its own mature discourse. This framework would serve better as a supplemental lens than as a primary ethics framework.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 2 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 02</span>
	<h2>Mental Health / Psychiatry</h2>
	<p>The highest-density natural fit of the framework — HIR was explicitly developed to restore coherence under conditions of fragmentation, pressure, and outsourced agency.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">2.1</span>
	<span class="app-name">Recovery-Oriented Mental Health Care</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	HIR's own origin statement — "developed as a framework for restoring coherence at the human core under conditions of fragmentation, pressure, and outsourced agency" — is indistinguishable from the goals of recovery-oriented mental health systems. The regenerative, non-brittle architecture (remaining terms can exert corrective pull after one is weakened) maps directly to the recovery model's rejection of linear, stage-based treatment in favor of non-linear, relapse-tolerant, person-directed trajectories. The non-identity, non-dogmatic position (governing relation not identity) aligns with the recovery model's emphasis on self-directed identity formation beyond illness label. The baseline-setting property maps to the therapeutic role of peer support workers and recovery coaches.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The framework was explicitly built for this domain. Recovery-oriented care's core principles (hope, personal agency, non-linear recovery, meaningful life beyond diagnosis) map directly to HIR's regenerative reclamation architecture.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The framework lacks psychiatric-specific variables (symptom burden, medication adherence, diagnostic criteria). It operates at the relational/values layer, not at the clinical symptom layer.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">2.2</span>
	<span class="app-name">Trauma Recovery and Post-Traumatic Growth</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The earned grit model (G = g(P, Rc, t)) — pressure engaged through realism, over recursive time, produces density rather than mere suffering — is structurally identical to the core mechanism in post-traumatic growth (PTG) literature. The framework's explicit statement that "suffering alone does not guarantee maturation; pressure must be engaged through realism" captures the key distinction between PTG (active, meaning-engaged processing) and trauma sequelae (unprocessed, avoidant, or dissociated responses). Alchemical Continuity (Ac) maps directly to the meaning-making capacity that PTG research identifies as central to growth after adversity. The non-brittle architecture maps to the documented finding that trauma survivors can sustain core relational functioning even under significant symptom burden.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Ac and G together constitute a formal model of the meaning-making + grit pathway that PTG researchers (Tedeschi, Calhoun) describe informally. The recursive contact model matches known trauma processing mechanisms.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The framework doesn't model neurobiological trauma mechanisms (HPA axis dysregulation, amygdala sensitization). It operates at the psychological-relational level, requiring external translation to clinical symptom measurement.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">2.3</span>
	<span class="app-name">Psychological Resilience Research and Measurement</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The S_core stability measure (s(H, I, R, Rn, G)) formalizes psychological resilience as an emergent property of constructive relational variables under sustained pressure. This maps to resilience frameworks (Masten, Luthar) that identify positive relational bonds, self-coherence, and adaptive meaning-making as resilience factors. The degradation trajectories in OAM model risk accumulation over time. The HIR density concept (mature grit turns alignment into ballast) maps to the concept of resilience not as mere bounce-back but as increased adaptive capacity after challenge.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Systems</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>S_core is a formal resilience index. The compound variable structure closely mirrors multi-factor resilience scales. OAM provides the complementary adversity-accumulation model that resilience researchers require.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Resilience measurement is contested in the literature. The PC framework would need operationalized measurement instruments before entering resilience research discourse.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">2.4</span>
	<span class="app-name">Chronic Relational Instability / Borderline Dynamics</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Borderline personality disorder's core features — chronic identity instability, relational fragmentation, emotional dysregulation — can be modeled within HIR as sustained low F (fidelity), low C (cohesion), and highly variable Rn (resonance) with high susceptibility to the δ distortion/decay term. The regenerative model is relevant: the clinical goal is to build earned density (G) through consistent therapeutic contact rather than to stabilize through compliance. The non-identity position (governing relation not identity) matches DBT's and schema therapy's emphasis on relational consistency over identity prescription.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR's regenerative architecture and the earned grit pathway model the long-arc therapeutic process for chronic relational dysregulation more accurately than brittle "treatment compliance" models.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>BPD has a well-developed evidence base (DBT, MBT). The PC framework adds a lens but is not a clinical protocol. Significant adaptation and operationalization would be required.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">2.5</span>
	<span class="app-name">Meaning-Centered Psychotherapy / Existential Approaches</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The Alchemical Continuity variable (Ac) — defined as "the living human capacity to convert pain, memory, grit, and experience into self-owned meaning, relation, and signal" — is a formal structural analog to the meaning-making capacity that underlies meaning-centered psychotherapy (Frankl, Breitbart), acceptance and commitment therapy, and narrative therapies. The OAM's tracking of Ac depletion as a driver of social harm and degradation formalizes why meaning-loss is clinically significant beyond mood symptoms. The loop closure concept maps to Frankl's emphasis on mortality awareness as a meaning-activating condition.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The Ac variable is the most clinically precise variable in the framework — its depletion pathway in the OAM matches well-documented pathways from meaning-loss to psychiatric and social harm.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>"Alchemical" is a term that may face clinical resistance. Operationalization of Ac into measurable psychotherapy outcomes would require careful definitional bridging.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 3 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 03</span>
	<h2>Rehabilitation / Recovery</h2>
	<p>Progressive loading, earned resistance, and non-brittle recovery architecture have natural analogues in physical and vocational rehabilitation.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">3.1</span>
	<span class="app-name">Physical Rehabilitation — Pressure, Grit, and Progressive Loading</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The earned grit model (G = g(P, Rc, t)) maps structurally to the principles of progressive loading in physical rehabilitation: calibrated pressure, recursive exposure, and temporal accumulation produce increasing structural density and resistance. The critical distinction — pressure without realism produces damage not maturation — maps to the clinical understanding that graded exercise must be appropriately dosed, contextualized, and paced. The "realism contact" requirement maps to the importance of patient self-awareness, feedback monitoring, and symptom reporting in rehabilitation progress.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Biological · Behavioral · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The formal structure of G (pressure + realism contact + time → density) is isomorphic with progressive loading principles, making this an unusually clean structural mapping.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The framework has no physiological variables (muscle fiber, neural plasticity, VO2max). The mapping is at the structural/motivational level; exercise science has its own validated progressional models.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">3.2</span>
	<span class="app-name">Cardiac and Pulmonary Rehabilitation Engagement</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The sustained engagement problem in cardiac/pulmonary rehabilitation (high drop-out, low long-term adherence) can be framed through the OAM degradation variables. Time poverty (W), financial strain (F), physiological strain (H), and social harm/agency loss (N) are OAM-modeled pressures that predict rehabilitation non-engagement more accurately than clinical severity alone. The HIR framework's non-identity position suggests rehabilitation programs that activate intrinsic meaning (Ac) rather than compliance pressure will sustain engagement more effectively.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Systems · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM degradation variables map directly to documented social and structural barriers to cardiac rehab completion, offering a multi-variable explanatory model for differential adherence.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Cardiology rehabilitation research has its own validated adherence prediction models. The framework's value here is as a framing complement, not a standalone predictor.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">3.3</span>
	<span class="app-name">Acquired Brain Injury Rehabilitation — Non-Brittle Recovery Framing</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The non-brittle architecture (weakening one term stresses but does not necessarily destroy the whole; remaining terms retain corrective pull) maps to the neurological reality of brain injury recovery — compensatory function, neuroplasticity, and the non-linear, domain-specific nature of ABI recovery. The regenerative reclamation property models the documented phenomenon of late-stage functional gains in ABI rehabilitation. The Ac variable maps to the identity reconsolidation challenge that acquired brain injury poses.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The non-brittle model explicitly rejects the assumption that partial system degradation is irreversible — which is the key principle in modern ABI rehabilitation.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>ABI rehabilitation is a highly specialized neurological discipline. The PC framework lacks neurological variables and would function as a patient-facing framing layer, not a clinical protocol.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">3.4</span>
	<span class="app-name">Vocational Rehabilitation and Workforce Re-Entry</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's structural drivers (compliance rigidity K, institutional penetration I, coercive enforcement M, financial strain F, time poverty W) model the systemic barriers that disabled and chronically ill individuals face in workforce re-entry. The HIR earned grit model (recursive pressure-contact under realism → increasing density) maps to the vocational development pathway. The non-identity position is directly relevant to the dignity-preserving framing of disability-inclusive employment.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Systems · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM provides a multi-variable degradation model that captures the interlocking systemic barriers to vocational re-entry better than single-variable models.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Vocational rehabilitation has a distinct, occupation-focused evidence base. This framework's contribution would be at the systems/structural framing layer.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 4 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 04</span>
	<h2>Pediatrics / Child Development</h2>
	<p>Developmental resilience, attachment dynamics, and the emerging impact of digital ecology on child agency all map to framework variables.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">4.1</span>
	<span class="app-name">Developmental Resilience and Adverse Childhood Experiences (ACEs)</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR framework maps directly to the protective relational conditions studied in the ACE and resilience literature. A high-HIR caregiving environment (honest, integrity-consistent, respectful) constitutes the relational bedrock that buffers ACE-related harm. The OAM's N equation — where social harm rises as Ac falls — models the documented pathway where meaning-capacity depletion under cumulative adversity drives developmental harm. The earned grit model maps to the developmental distinction between adversity that builds capacity (engaged, supported) and adversity that damages (unsupported, unprocessed). The baseline-setting property maps to the documented protective effect of a single stable adult on developmental outcomes.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR relational variables precisely describe the buffering relational conditions identified in ACE research. The non-brittle grit model matches the developmental resilience literature's emphasis on supported adversity as capacity-building.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>ACE research has its own validated score instruments and longitudinal datasets. The PC framework would need operationalized variables that can cross-reference with existing ACE measurement systems.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">4.2</span>
	<span class="app-name">Pediatric Digital Health / Screen Time and Cognitive Outsourcing</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's cognitive outsourcing variables — Social Feed Saturation (S), Mobile Mediation (C), AI Offloading (A), and Hyperstimulation/Numbing (X) — map directly to documented risk pathways in pediatric screen time research. The T (Total Cognitive Outsourcing Load) composite maps to emerging pediatric digital exposure indices. The Alchemical Continuity depletion pathway (loss of capacity to convert experience into self-owned meaning) maps to documented effects of high social media use on adolescent identity formation and meaning coherence.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral · Systems</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM cognitive outsourcing variable set (S, A, C, X, T) was built to model exactly the digital ecology conditions now documented in pediatric health research literature.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Pediatric screen time research is contested and rapidly evolving. The OAM variables, while structurally aligned, require operationalized pediatric-specific measurement.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">4.3</span>
	<span class="app-name">Attachment-Based Parenting Support</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	HIR in the parent-child dyad: parental Honesty (consistent accurate representation of reality to the child), Integrity (continuity between stated values and actual behavior), and Respect (regard for child dignity, boundaries, and developing agency) are the structural foundations of secure attachment. The baseline-setting property maps to the empirically documented phenomenon of parental affect regulation transmitting to infant neurological regulation. The regenerative model maps to the evidence that disrupted attachment can be repaired through consistent corrective relational experience.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR in parenting context maps closely to documented secure attachment predictors (sensitivity, consistency, mind-mindedness). The non-brittle restorative model supports earned secure attachment frameworks.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Attachment theory has its own highly developed measurement and intervention literature (AAI, Circle of Security). The PC framework would function as a complementary framing layer.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">4.4</span>
	<span class="app-name">School-Based Social-Emotional Learning (SEL)</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR constructive sequence (H+I→F, R+I→C, F+C→Rn) maps to SEL competency frameworks: Honesty to self-awareness and social awareness; Integrity to responsible decision-making; Respect to relationship skills. The earned grit model maps to growth mindset and academic perseverance literature. The non-identity position (governing relation not identity) is directly relevant to inclusive, identity-affirming SEL implementation.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR provides a simple, teachable constructive framework that maps well to SEL curriculum logic at the elementary and secondary level.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>SEL has validated frameworks (CASEL) with extensive research backing. The PC framework's value would be as a conceptual complement or curriculum lens.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 5 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 05</span>
	<h2>Palliative / Hospice / End-of-Life Care</h2>
	<p>The loop closure concept — death as completion condition rather than negation — gives this framework unusual structural alignment with palliative principles.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">5.1</span>
	<span class="app-name">Dignified Dying and Loop Closure Framework</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The loop closure concept — "death functions as loop closure: not as mere negation, but as the completion condition that makes room for renewal, nutrient return, and further growth" and the statement that "where closure is understood as part of continuity, fear of mortality should taper" — maps directly to the palliative care principle of death as a natural life completion, not a clinical failure. This is not a common property of behavioral frameworks; most treat death as an outside boundary condition rather than an integrated structural term. The HIR baseline-setting property maps to the established palliative principle that a calm, coherent presence at the bedside (clinician, family, chaplain) can stabilize the dying person's experience.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Social-support · Cognitive</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Loop closure is architecturally integrated into the framework, not added externally. This makes the PC framework one of the few non-religious formal frameworks that treats death as a meaningful structural component rather than a limit condition.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Palliative care is a highly specialized medical discipline with its own validated outcome measures (PCAOMS, NRS symptom scales). The PC framework operates at the existential/relational layer and would require integration with clinical protocols.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">5.2</span>
	<span class="app-name">Meaning-Making in Serious Illness</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Alchemical Continuity (Ac) — the capacity to convert pain, memory, grit, and experience into self-owned meaning — is the central palliative psychological resource. Its depletion trajectory in the OAM captures the progression from illness-related meaning disruption to existential despair. The framework's non-identity position is relevant to palliative care's emphasis on the patient's own values and priorities driving end-of-life decisions. The HIR fidelity variable maps to the life review process (honest integration of life narrative) central to palliative dignity therapy.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Ac is a direct structural analog to meaning-making capacity as defined in palliative psychology literature (Breitbart, Kissane). Its depletion pathway has direct clinical relevance to existential suffering in serious illness.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Meaning-centered psychotherapy for palliative patients has validated protocols (MCAP). The PC framework would need to demonstrate additional value beyond existing validated approaches.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">5.3</span>
	<span class="app-name">Anticipatory Grief and Family Preparation</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR framework's Cohesion variable (R+I → relational structural fit) maps to the family relational coherence that palliative care research identifies as a protective factor in bereavement outcomes. The regenerative architecture — remaining terms can help recover weakened structures — maps to the family grief trajectory. OAM's N (social harm/agency loss) models anticipatory grief's disruption of everyday agency and meaning. The baseline-setting property maps to the role of a coherent family member or chaplain in stabilizing the family system during terminal illness.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Social-support · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR Cohesion and the non-brittle architecture describe family relational dynamics under anticipatory grief more accurately than collapse-model frameworks.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Family bereavement research has its own validated measurement tools. Operationalizing family-level HIR variables would require significant instrument development.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">5.4</span>
	<span class="app-name">Death Anxiety and Existential Distress in Clinical Settings</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The framework's treatment of loop closure as continuity rather than negation, and the stated property that "where closure is understood as part of continuity, fear of mortality should taper," provides a formal structural basis for interventions that address death anxiety through meaning and continuity rather than denial or suppression. This maps to terror management theory's positive arm and to documented findings on reduced death anxiety in highly meaning-integrated individuals.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The loop closure concept provides an unusual, non-religious formal basis for existential integration that has direct clinical relevance to death anxiety management.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>This remains a conceptual mapping until empirical work connects PC variables to validated death anxiety measures (DAS, MFODS).</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 6 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 06</span>
	<h2>Addiction / Substance-Use Recovery</h2>
	<p>OAM's agency erosion model and HIR's non-brittle reclamation architecture together constitute an unusually comprehensive structural framework for addiction.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">6.1</span>
	<span class="app-name">Substance Use Disorder — Agency Loss and Structural Recovery</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's agency erosion model provides a formal structural description of addiction's core dynamic: progressive displacement of autonomous judgment by externalized compulsive behavior. The N equation (social harm rising as Ac falls) models the documented co-occurrence of meaning depletion and escalating substance use. The HIR reclamation architecture models recovery as a non-linear, regenerative process where remaining relational integrity can anchor restoration — mapping directly to the attachment and social bond literature in addiction recovery. The earned grit model (pressure engaged through realism over recursive time) maps to the therapeutic pathway in evidence-based addiction treatment.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM and HIR together constitute a formal model of the addiction/recovery cycle: OAM models the degradation trajectory; HIR models the reclamation pathway. Both include the Ac/meaning variable that addiction recovery research identifies as central.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Addiction has well-established neurobiological models (dopaminergic reward circuit, stress sensitization). The PC framework operates at the behavioral/relational layer and requires external translation to neurobiological mechanisms.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">6.2</span>
	<span class="app-name">Behavioral Addictions (Gambling, Gaming, Social Media)</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM cognitive outsourcing variables (S, A, C, X) were explicitly built to model the digital behavioral addiction ecology. Social Feed Saturation (S) directly models algorithmic behavioral conditioning; Hyperstimulation/Numbing (X) models dopaminergic blunting; Mobile Mediation (C) models device-mediated identity displacement. The T (Total Cognitive Outsourcing Load) composite is a multi-variable behavioral addiction index that maps to documented multi-screen, multi-platform risk loading.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Systems</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM cognitive outsourcing variable set was designed specifically to model digital behavioral ecology pathologies — making this one of the most direct fit areas in the entire inventory.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Behavioral addiction diagnostic criteria are still evolving (ICD-11 gaming disorder). The OAM model would need validation against clinical samples rather than population-level simulation.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">6.3</span>
	<span class="app-name">Recovery Milieu Design and Peer Support Architecture</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR baseline-setting property — a dense HIR core establishes local coherence conditions that may increase fidelity and cohesion in the surrounding field — is a formal model for how recovery milieus, sober living environments, and peer support networks function. A high-HIR peer support worker or sponsor sets coherence conditions that the person in early recovery can orient toward or relax into. The non-identity position is directly relevant to peer support's emphasis on non-prescriptive, lived-experience-based accompaniment rather than compliance authority.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Behavioral · Systems</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The baseline-setting property provides a formal mechanism for why peer support works — not through instruction, but through coherence transmission — which maps to documented findings on peer-delivered recovery support.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The baseline-setting property is descriptive and architectural; it does not specify how to train peer workers or measure milieu coherence in practice.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">6.4</span>
	<span class="app-name">Structural and Social Determinants of Addiction</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The compounding OAM degradation model — where ideological saturation (R), compliance rigidity (K), institutional penetration (I), financial strain (F), time poverty (W), and physiological strain (H) interact multiplicatively to drive agency loss — provides a formal multi-variable model of the structural determinants of addiction. This maps to Gabor Maté's framework of addiction as a response to social disconnection and unprocessed pain, but provides a more formally specified variable architecture that could support quantitative social research.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM variables capture the multi-dimensional structural risk environment for substance use disorders at a level of specificity that single-variable SDOH models do not.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM coefficients are currently provisional. Structural addiction research uses population-level datasets that would need to be used to calibrate OAM parameters.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 7 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 07</span>
	<h2>Genomics / Uncertainty Modeling</h2>
	<p>The weakest biological mappings in this inventory. Included with explicit speculative labeling.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">7.1</span>
	<span class="app-name">Epistemic Uncertainty in Clinical Decision-Making</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The bounded variable system [0,1] with clamping constraints, provisional coefficients, and temporal update rules provides a structural model of uncertain, bounded reasoning under compound variables — directly applicable to clinical decision-making under uncertainty. The framework's explicit acknowledgment of provisional vs. canonical status (evidence status classification system in file 002) maps to Bayesian uncertainty reasoning in clinical reasoning research.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Cognitive</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The variable architecture (bounded, clamped, compound, provisional) provides formal structure useful for teaching clinical uncertainty reasoning.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Clinical decision-making under uncertainty has its own validated frameworks (Bayesian reasoning, decision trees, fast-and-frugal heuristics). PC's contribution here is structural/pedagogical.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">7.2</span>
	<span class="app-name">Multi-System Disease Risk — Compounding Interaction Modeling</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM's multiplicative interaction terms (R×K×I×P×N×E) model non-linear compounding of risk factors in a way that is structurally similar to polygenic risk score modeling and gene-environment interaction frameworks. The formal demonstration (300-year simulation) that linear single-variable models underestimate long-horizon degradation is methodologically relevant to chronic disease epidemiology. This is a formal structural mapping, not a biological mechanism claim.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Multiplicative non-linear compound risk factor architecture is a known gap in many epidemiological risk models; OAM's mathematical structure demonstrates this pattern with explicit temporal modeling.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM variables are behavioral/social, not biological. Direct transfer to genomic risk modeling requires variable translation and biological validation.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">7.3</span>
	<span class="app-name">Canalization and Developmental Buffering — Structural Analogy</span>
	<span class="confidence-badge badge-weak">Weak / Speculative</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Waddington's canalization concept (developmental pathways buffered against perturbation) is formally analogous to the HIR baseline-seeking, self-maintenance architecture (Axiom 1: what is primordial must preserve its identity under pressure). The non-brittle model (partial term weakening doesn't collapse the whole) maps loosely to genetic buffering mechanisms. This is a structural/conceptual analogy with no direct biological variable mapping.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Biological (analogical only)</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Formal structural analogy to canalization: self-maintaining, non-brittle, baseline-seeking systems in development.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>This is a pure conceptual analogy with no shared variables, mechanisms, or empirical basis. Should be used only for conceptual bridge-building in academic contexts, not as a biological claim.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 8 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 08</span>
	<h2>Neurology / Brain / Cognition</h2>
	<p>Best fits are at the cognitive-outsourcing and degradation-trajectory levels, not at the neurological mechanism level.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">8.1</span>
	<span class="app-name">Cognitive Reserve and Digital Cognitive Outsourcing</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM's AI Offloading (A), Social Feed Saturation (S), Mobile Mediation (C), and Hyperstimulation/Numbing (X) composite (T = total cognitive outsourcing load) models the displacement of active cognitive engagement by technology-mediated passivity. This maps to the cognitive reserve literature, where active cognitive engagement — problem solving, social navigation, meaning-making — builds protective reserve. T increase models reserve depletion through outsourcing. The Ac variable maps to the personal meaning-making and autobiographical coherence that cognitive reserve researchers identify as protective against dementia onset.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Systems</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The cognitive outsourcing variables provide a multi-dimensional model of active cognitive engagement depletion — directly relevant to cognitive reserve building and protection research.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Cognitive reserve is neurologically defined. The PC model operates at the behavioral/exposure level; it would need neurocognitive validation to make reserve-related claims.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">8.2</span>
	<span class="app-name">Progressive Neurological Disease — Degradation Trajectory Modeling</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM's temporal accumulation model (D[t+1] compounding with non-linear multiplicative terms over a 300-year simulation) provides a formal structural analog to progressive neurological disease trajectory modeling. The non-brittle HIR architecture maps to the documented phenomenon of preserved relational capacity in early and mid-stage neurological decline, and to dignity-preserving care approaches in neurodegenerative disease. This mapping is at the trajectory/systems level, not at the biological mechanism level.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Behavioral · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The temporal degradation architecture (non-linear, compounding, multi-variable) matches the documented trajectory of progressive neurological conditions better than linear decline models.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Neurological disease progression is biologically defined. OAM variables are social/behavioral. The mapping is structural/analogical and does not constitute a neurology model.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">8.3</span>
	<span class="app-name">Executive Function, Self-Regulation, and Impulse Control</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR Integrity variable — "structural continuity between principles, decisions, and actions" — is a behavioral-level description of executive function's core task: bridging values, deliberation, and action in a temporally coherent way. The earned grit model maps to the delayed-gratification and effortful control literature. The OAM cognitive outsourcing load (T) models the executive function depletion pathways documented in sustained attention, working memory, and inhibitory control research under high media load.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Cognitive · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Integrity's formal definition (structural continuity between principles, decisions, and actions) is an unusually precise behavioral description of executive function's integrative role.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Executive function is a neuropsychological construct with validated measurement instruments (BRIEF, Stroop, WCST). PC variables lack the specificity for direct neuropsychological mapping.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">8.4</span>
	<span class="app-name">Consciousness and Global Coherence Theories — Structural Analogy</span>
	<span class="confidence-badge badge-weak">Weak / Speculative</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The Resonance (Rn) construct — "living coherence produced through recursive reinforcement of fidelity and cohesion" — has structural analogies to global workspace theory and integrated information theory frameworks, which describe consciousness as emerging from coherent information integration across subsystems. This is a pure structural analogy with no shared empirical basis.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Biological (highly speculative)</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Structural analogy: Rn as emergent coherence from recursive integration of sub-states mirrors global workspace / IIT frameworks.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>No shared variables, no shared empirical basis, no mechanistic bridge. This should be flagged as purely speculative if raised in any clinical context.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 9 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 09</span>
	<h2>Physiological Regulation / Biofeedback</h2>
	<p>Allostatic load is the strongest physiological mapping. "Coherence" in biofeedback and the framework's Rn are not mechanistically connected — naming similarity should not be treated as structural fit.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">9.1</span>
	<span class="app-name">Allostatic Load and Chronic Stress Modeling</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's physiological strain index (H[t]), accumulated degradation (D[t]), time poverty (W[t]), financial strain (F[t]), and ecological strain (E[t]) collectively constitute a formal behavioral-systems model of allostatic load — the cumulative biological cost of chronic stress adaptation. The compounding multiplicative trajectory in OAM matches the documented non-linear accumulation of allostatic burden. The 300-year temporal simulation demonstrates multi-generational stress accumulation dynamics, relevant to epigenetic and intergenerational trauma research.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Biological · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM variable set (H, W, F, E, N, D with compounding interactions) directly maps to the multi-domain biological burden that allostatic load measures (McEwen's biomarker composite).</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Allostatic load is biologically defined (cortisol, HPA axis, cardiovascular, metabolic markers). OAM captures social/behavioral drivers of allostatic load, not the biological load itself. The mapping is to the upstream driver model, not the biomarker.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">9.2</span>
	<span class="app-name">Autonomic Dysregulation in Trauma — Behavioral Layer</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM physiological strain index (H[t]) and the HIR resonance decay variable (δ — local distortion, decay, or disruption) provide a behavioral-systems framing of autonomic dysregulation that is relevant to trauma-informed somatic therapy contexts. The regenerative HIR model — remaining terms retain corrective pull after disruption — maps to polyvagal-informed window-of-tolerance frameworks. This is a behavioral/systems mapping, not a direct neurophysiological claim.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Biological (structural analogy only)</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The non-brittle resonance model maps structurally to the window-of-tolerance concept: the system can sustain activation without collapse if remaining regulatory capacity is intact.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Autonomic dysregulation is a neurophysiological phenomenon. The mapping is at the behavioral/relational level. No direct physiological variables exist in the framework.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">9.3</span>
	<span class="app-name">Heart Rate Variability / HeartMath-Style Coherence Biofeedback</span>
	<span class="confidence-badge badge-weak">Weak / Speculative</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The term "coherence" in HeartMath biofeedback refers to a specific physiological state (HRV power spectrum pattern, sine-wave-like oscillation). The framework's Rn (Resonance) and C (Cohesion) variables are relational-behavioral constructs. The naming similarity is not a structural fit. There is no shared mechanism. This should not be used to imply that HIR practice produces HeartMath-measurable physiological coherence without empirical validation.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Biological (naming analogy only)</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The term "resonance" is shared. The framework's relational coherence may correlate with HRV-measured coherence but this has not been tested.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>HRV coherence is a specific physiological measurement. HIR resonance is a relational-behavioral construct. Conflating them without empirical bridge studies would be a misleading claim. Do not map this without data.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 10 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 10</span>
	<h2>Infectious Disease / Post-Viral Dysregulation</h2>
	<p>Best fits are at the systems/population-pressure and meaning-disruption levels, not at the immunological or virological level.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">10.1</span>
	<span class="app-name">Social Determinants of Infectious Disease Susceptibility</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's compound degradation variables (physiological strain H, financial strain F, time poverty W, ecological strain E, social harm N) model the multi-domain social determinants of health that consistently predict differential infectious disease susceptibility and severity. The population response variable P[t] models herd-level behavioral response dynamics relevant to disease transmission modeling.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM provides a multi-variable structural model of the social conditions that drive differential disease vulnerability — addressing a documented gap in epidemiological models that treat SDOH as additive rather than multiplicatively compounding.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>The OAM lacks immunological or virological variables. Its contribution is to the upstream social determinants layer, not to disease transmission modeling.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">10.2</span>
	<span class="app-name">Long COVID / Post-Viral Syndrome — Psychosocial and Meaning Layer</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Long COVID's documented psychosocial profile includes Alchemical Continuity depletion (inability to convert prolonged illness experience into coherent self-narrative), agency loss (loss of predictable bodily agency), and compounding multi-system degradation (D[t] analogy). The OAM physiological strain variable (H[t]) maps to the multi-system nature of Long COVID burden. The non-brittle HIR architecture is clinically relevant to the documented importance of maintaining partial functional identity despite fluctuating symptom load.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Systems · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The Ac depletion model and non-brittle architecture are directly relevant to the documented psychosocial complexity of Long COVID, where symptom fluctuation disrupts stable identity and meaning.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Long COVID involves active biological mechanisms (neuroinflammation, dysautonomia) that the PC framework does not model. The mapping is at the psychosocial management layer only.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">10.3</span>
	<span class="app-name">Pandemic-Scale System Pressure Modeling</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The 300-year OAM simulation provides a multi-variable compounding degradation trajectory model that is structurally relevant to pandemic-scale public health pressure modeling. The interactions between institutional penetration (I), compliance rigidity (K), physiological strain (H), coercive enforcement (M), and agency loss (N) capture documented pandemic-era health system dynamics. The population response variable P[t] provides a behavioral response multiplier analogous to behavioral epidemiology models.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM variables (K, I, M, H, N) directly model the institutional-behavioral dynamics documented in pandemic-era public health research.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Epidemiological modeling (SIR, SEIR) uses transmission-specific variables not present in OAM. The framework contributes a behavioral/institutional complement, not an epidemiological model.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">10.4</span>
	<span class="app-name">Health Behavior Change Under Collective Stress</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR framework's coherence-under-pressure architecture and the OAM's agency erosion model together provide a structural basis for understanding differential health behavior change under collective social stressors. High HIR individuals (strong fidelity, cohesion, earned grit) are modeled as more resistant to behavioral regression under OAM-type pressure. This maps to the documented relationship between psychological coherence and health behavior adherence under adversity.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The HIR/OAM contrast provides a formal model of differential behavioral resilience under collective stress — directly relevant to health promotion and disease prevention research.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Health behavior change models (TTM, SCT, PRIME) have validated measurement instruments. The PC framework would need operationalization to contribute to this empirical literature.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 11 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 11</span>
	<h2>Oncology / Cancer Signaling and Dysregulation</h2>
	<p>Strongest fits are at the care-process and meaning-making levels. Biological cancer mechanism mapping is not supportable and is labeled accordingly.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">11.1</span>
	<span class="app-name">Meaning-Making and Alchemical Continuity in Oncology Care</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Cancer diagnosis is a major Ac (Alchemical Continuity) stressor — it requires the patient to convert a profound and unwanted experience into self-owned meaning without collapsing identity. The OAM's Ac depletion pathway models the documented progression from meaning disruption to psychological and social harm in oncology patients. The loop closure framework provides a non-religious formal basis for the meaning-making work that palliative oncology identifies as central to quality of life outcomes.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Ac is the most directly applicable variable to oncology psychosocial care — its definition precisely captures the meaning-conversion challenge that oncology patients and their families face.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Oncology has validated psychosocial instruments (FACT, EORTC QLQ). The PC framework would need to demonstrate additive value beyond existing quality-of-life measurement frameworks.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">11.2</span>
	<span class="app-name">Oncology Care Team Integrity and Communication Quality</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	HIR in the oncology team context: Honesty maps to prognostic transparency and truth-telling in oncology communication; Integrity maps to consistent follow-through on care commitments; Respect maps to patient dignity preservation under treatment burden. The OAM's institutional penetration (I) and compliance rigidity (K) model documented barriers to patient-centered oncology communication in institutional settings.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Care-process · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Oncology communication quality research specifically identifies the H, I, R variables (honesty in prognosis, consistency in care, dignity in interaction) as key drivers of patient trust and treatment adherence.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Oncology communication has its own validated training frameworks (SPIKES, Serious Illness Conversation Guide). The PC framework would serve as a complementary framing.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">11.3</span>
	<span class="app-name">Patient-Family Cohesion Support During Cancer Treatment</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR Cohesion variable (R+I → relational structural fit) and the HIR baseline-setting property map to documented findings that family relational coherence during cancer treatment predicts patient quality of life and family bereavement outcomes. The non-brittle architecture models the family's capacity to maintain relational function under extreme illness-related stress.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The Cohesion variable in a family-systems context maps to validated findings on family relational quality as a cancer care outcome predictor.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Family-focused oncology support research uses validated instruments (FEI, FAM). Operationalization of PC Cohesion at the family level would require significant instrument development.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">11.4</span>
	<span class="app-name">Cancer as Cellular Coherence Breakdown — Structural Metaphor Only</span>
	<span class="confidence-badge badge-weak">Weak / Speculative</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Some frameworks describe cancer as a breakdown of cellular coherence — loss of differentiated identity, boundary violation, and uncontrolled propagation. These properties have surface analogies to HIR degradation and OAM fault conditions. This is a structural metaphor only and must not be presented as a biological cancer mechanism claim. The framework has no biochemical variables.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Biological (metaphorical only)</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>Structural metaphor: cancer as loss of cellular identity coherence and boundary-respecting behavior has surface analogy to HIR degradation dynamics.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Not a biological claim. No shared mechanism. Presenting this in clinical oncology contexts as anything more than a heuristic metaphor would be a misrepresentation. Do not use this mapping without explicit labeling as metaphor.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 12 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 12</span>
	<h2>Disability / Chronic Illness Support</h2>
	<p>Three of the strongest application areas in the entire inventory cluster here — dignity, non-brittle self-management, and institutionalization critique.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">12.1</span>
	<span class="app-name">Dignity-Based Disability Support and Autonomy Preservation</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The Respect variable's formal definition — "regard for dignity, boundaries, consequence, and shared life" — and the framework's non-identity position (governing relation not identity; not a gatekeeping system) align closely with disability rights frameworks (CRPD, nothing about us without us). The OAM's institutionalization variables (compliance rigidity K, institutional penetration I, coercive enforcement M) provide a formal degradation model of what happens to disabled individuals under coercive institutional systems — precisely the critique that disability rights advocates have documented empirically.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Systems · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR's non-identity position and Respect's boundary definition match disability rights principles unusually well. OAM's institutionalization variables provide a formal model of documented institutional harm.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Disability advocacy has its own mature rights-based discourse. The PC framework would serve as a formal structural complement, not a replacement for disability rights frameworks.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">12.2</span>
	<span class="app-name">Chronic Illness Self-Management — Non-Brittle Trajectory Model</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Chronic illness self-management is characterized by fluctuation, partial function, flare-and-remission cycles, and the need to maintain life quality and identity under sustained challenge. The HIR non-brittle architecture — remaining terms retain corrective pull even when one is weakened — is a direct structural model of chronic illness management. The regenerative reclamation property models remission and partial recovery. The distinction between mere suffering and earned grit (realism engagement required) maps to the self-management difference between passive suffering and active coping with meaningful engagement.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The non-brittle, regenerative architecture was designed for exactly this type of fluctuating-under-pressure system — making this a natural structural fit rather than a forced one.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Chronic illness self-management research uses validated instruments (Patient Activation Measure, PROMIS). The PC framework needs operationalization to integrate with existing measurement frameworks.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">12.3</span>
	<span class="app-name">Institutionalization and Agency Erosion in Disability Contexts</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's core variables (K: compliance rigidity, I: institutional penetration, M: coercive enforcement, N: social harm/agency loss, q: agency erosion sensitivity) constitute a formal mathematical model of institutionalization harm that disability researchers have documented qualitatively for decades. The D[t] compounding degradation trajectory models the accumulation of institutional harm over time. The Alchemical Continuity depletion pathway models the documented loss of self-narrative capacity under prolonged institutional control.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Social-support · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM was explicitly built to model agency erosion under institutional pressure — which is precisely the dynamic that disability researchers identify as the core mechanism of institutional harm.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM coefficients are provisional. Applying this to disability policy analysis would require calibration against disability-specific data and co-design with disability advocates.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">12.4</span>
	<span class="app-name">Adaptive Identity Under Chronic Condition and Variable Capacity</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR non-identity position (governing relation not identity; allowing identities to coexist without mutual degradation) is directly relevant to the identity renegotiation challenge in chronic illness and disability — where pathologizing identity models do additional harm. The framework's support for identity plurality and non-conformity maps to disability identity frameworks that reject the medical deficit model.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Behavioral · Cognitive · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The non-identity position is philosophically aligned with disability studies' rejection of medicalized identity framing.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Disability identity is a complex discourse area. The PC framework should not be presented as a disability theory without engagement with disability studies scholars.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 13 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 13</span>
	<h2>Homelessness / Dignity Restoration / Community Care</h2>
	<p>OAM's multi-domain degradation model and HIR's dignity and agency architecture provide an unusually comprehensive framework for homelessness and social reintegration.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">13.1</span>
	<span class="app-name">Housing-First and Dignity Restoration</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Housing-First's core theoretical claim — that stable housing provides the foundation from which other recovery supports can build, rather than requiring prior recovery to earn housing — maps directly to the HIR bedrock concept: a stable relational/dignity foundation is necessary before higher-order capacities (fidelity, cohesion, resonance) can emerge. The Respect variable (regard for dignity, boundaries, shared life) is the formal expression of Housing-First's dignity-first principle. OAM variables (F: financial strain, W: time poverty, N: social harm/agency loss, H: physiological strain, M: coercive enforcement) model the compounding degradation profile of homelessness.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Systems · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The HIR bedrock model and the Respect dignity definition provide formal structural support for Housing-First's foundational claim. OAM models the multi-domain degradation that homelessness represents.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Housing-First has its own evidence base (Pathways Housing First, At Home/Chez Soi trials). The PC framework would serve as a theoretical framing complement, not a policy replacement.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">13.2</span>
	<span class="app-name">Re-Entry from Incarceration and Social Reintegration</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's coercive enforcement index (M) and institutional penetration (I) model the institutionalization dynamics of incarceration. The regenerative HIR reclamation architecture models reintegration as a non-linear process of rebuilding fidelity, cohesion, and resonance rather than a compliance milestone process. The earned grit framework provides a non-punitive developmental model for transformation under adversity. The non-identity position maps to rehabilitative approaches that do not require prescribed identity change.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Systems · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM captures incarceration's institutional degradation dynamics; HIR's regenerative model provides a non-compliance framework for reintegration that matches evidence-based reentry supports.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Reentry research has validated risk/needs frameworks (Andrews & Bonta). The PC framework would serve as a values/meaning-layer complement.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">13.3</span>
	<span class="app-name">Community Social Fabric and Mutual Aid Network Sustainability</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR baseline-setting property — a dense HIR core sets local coherence conditions — models how high-integrity community anchors (mutual aid organizers, trusted elders, coherent community institutions) establish local social fabric. The Cohesion variable (R+I) maps to documented community cohesion factors in public health. The OAM's social harm (N) and accumulated degradation (D) model community fabric dissolution under sustained systemic pressure.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The baseline-setting property formally models how community health anchors function — a mechanism that social capital researchers describe informally but rarely formalize mathematically.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Community cohesion research uses validated population-level measures. The PC framework would need operationalization to integrate with community health surveys.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">13.4</span>
	<span class="app-name">Poverty-Related Health Disparities — Multi-Variable Structural Model</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's financial strain (F), time poverty (W), physiological strain (H), social harm/agency loss (N), and accumulated degradation (D) variables constitute a multi-domain poverty-health pathway model. The multiplicative compounding of these variables in the D equation models the documented non-linear relationship between poverty severity and health outcomes that single-variable models miss. The Ac depletion pathway (meaning-making capacity loss under poverty stress) maps to documented pathways between chronic economic stress and mental health deterioration.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM's multi-variable compound model is structurally suited to capturing poverty's multi-dimensional health impacts better than additive SDOH checklists.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM coefficients are provisional and based on simulated rather than empirical calibration. Integration with poverty health research would require empirical coefficient calibration.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 14 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 14</span>
	<h2>Public Health / Systems Pressure</h2>
	<p>OAM's simulation engine was built for population-scale dynamics. This is one of the highest-density application zones in the inventory.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">14.1</span>
	<span class="app-name">Social Determinants of Health — Multi-Variable Compounding Model</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	OAM's full variable set (F, W, H, N, E, M, K, I, R, Ac, D) covers the principal SDOH domains recognized by WHO and CDC frameworks: economic stability (F), social context (N), education and information (T, Ac), health and healthcare (H), neighborhood and built environment (E, L). The multiplicative compounding architecture captures documented non-linear interactions between SDOH factors. The 300-year temporal simulation demonstrates that SDOH effects compound over intergenerational time horizons that single-decade studies miss.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM variable set covers the principal SDOH domains and provides a compounding interaction architecture that single-variable SDOH models lack. The temporal simulation adds a dimension absent from most SDOH frameworks.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM coefficients are currently provisional. Population-level validation with empirical datasets would be required before policy application.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">14.2</span>
	<span class="app-name">Population-Level Burnout, Exhaustion, and System-Wide Demoralization</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The compounding accumulation of time poverty (W), physiological strain (H), hyperstimulation/numbing (X), and Alchemical Continuity depletion (1-Ac) in the OAM models population-level burnout and moral demoralization as a systems phenomenon, not as an individual failure. The distinction between mere suffering and earned grit (realism engagement required) maps to the documented difference between passive exhaustion and constructive collective adaptation. The HIR reclamation architecture models recovery pathways from collective demoralization.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM explicitly models the variable set (W, H, X, Ac) that describes population-level demoralization. The framework is one of very few that formalizes burnout as a multi-variable systems phenomenon rather than an individual deficit.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Population-level wellbeing is measured through large survey instruments. PC variables would need empirical operationalization and survey instrument development.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">14.3</span>
	<span class="app-name">Long-Horizon Public Health Simulation and Policy Planning</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The 300-year OAM simulation with 14+ interacting variables, documented temporal trajectories, and sensitivity to initial conditions provides a formal model architecture relevant to long-horizon public health simulation and policy planning. The simulation demonstrates how early interventions (reducing R, K, or I; increasing Ac) alter degradation trajectories substantially over multi-decade time horizons — a formally specified claim with direct policy relevance.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The OAM is one of few non-epidemiological behavioral frameworks with an explicit multi-century simulation record, demonstrating long-horizon sensitivity to initial conditions — a property directly relevant to policy planning.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>OAM simulation outputs require empirical calibration before policy application. The simulation architecture is sound; the coefficient values remain provisional.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">14.4</span>
	<span class="app-name">Structural Violence and Health Inequality — Formal Mechanism Model</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Paul Farmer's structural violence framework identifies how social structures (inequality, racism, institutional exclusion) damage health through invisible, chronic mechanisms. OAM formalizes these mechanisms: ideological saturation (R), compliance rigidity (K), institutional penetration (I), coercive enforcement (M), and their compounding product in the N and D equations. This provides a formal mathematical specification of structural violence's degradation mechanism that Farmer's framework describes verbally.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM's structural degradation mechanism variables are a formal specification of the informal structural violence model — providing mathematical architecture to a well-recognized but under-formalized framework.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Structural violence research is rooted in political economy and ethnography. Some scholars in this tradition may resist formalization. Community engagement would be essential.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">14.5</span>
	<span class="app-name">Environmental Health and Ecological Strain as Public Health Driver</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM's Ecological Strain index (E[t]) and Resource Extraction Strain (L[t]) model the documented health consequences of environmental degradation as a function of institutional behavior (R×K×P[t] compound). The Cooling Water Burden (Wc[t]) provides a specific infrastructure-level variable relevant to planetary health. The model's formal demonstration that ecological and social harm interact multiplicatively (rather than additively) maps to the One Health framework's core premise.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Biological</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM's explicit ecological variables (E, L, Wc) and their interaction with social harm variables map to planetary health and One Health frameworks that require social-ecological system modeling.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Environmental health uses biologically validated exposure models. OAM's ecological variables would need linkage to actual environmental monitoring data to serve environmental health research.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 15 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 15</span>
	<h2>Caregiver Support / Family Support</h2>
	<p>Caregiver depletion, family system coherence, and peer support integrity are natural fit areas for the HIR-OAM combined architecture.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">15.1</span>
	<span class="app-name">Caregiver Burden and Depletion Modeling</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Caregiver burden maps directly to HIR depletion under sustained OAM pressure: the caregiver's Honesty (honest acknowledgment of limits), Integrity (role consistency), and Respect (for self and care recipient) are chronically challenged by time poverty (W), physiological strain (H), financial strain (F), and agency loss (N) — all OAM variables. The Alchemical Continuity (Ac) depletion pathway models caregiver compassion fatigue as a meaning-conversion capacity loss. The non-brittle architecture models caregiver resilience and the partial recovery capacity that prevents terminal burnout when support interventions are introduced.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Behavioral · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM variables (W, H, F, N, Ac) directly model the multi-domain burden that caregiver research consistently identifies. The Ac depletion pathway captures compassion fatigue with unusual precision.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Caregiver burden has validated measurement instruments (Zarit Burden Interview, CBI). PC variables would need instrument operationalization to integrate with this literature.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">15.2</span>
	<span class="app-name">Family Systems Coherence and Support Planning</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	HIR at the family systems level: Cohesion (R+I) maps to family relational coherence; the non-brittle architecture maps to family systems theory's documented capacity for regeneration after disruption; the baseline-setting property maps to the role of a highly coherent family member in stabilizing the family system under stress. The B_local = b(S_core) expression formally models how a high-density member sets local coherence conditions for the family field.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Social-support · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR Cohesion and the baseline-setting property map to validated findings in family systems research on relational coherence and the anchor-member phenomenon.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Family systems therapy has well-developed models (Bowen, structural, narrative). PC would serve as a complementary framing layer rather than a clinical protocol replacement.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">15.3</span>
	<span class="app-name">Peer Support Worker Role Integrity and Sustainability</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	Peer support workers occupy a uniquely integrity-demanding role: their effectiveness depends on Honesty (about their own experience), Integrity (consistency between lived experience and practice), and Respect (for the autonomy and dignity of those they support). The baseline-setting property formally models how a high-HIR peer support worker establishes local coherence conditions for the people they support — making this the formal mechanism of peer support transmission. The OAM institutional variables (K, I, M) model how formalizing and bureaucratizing peer support roles degrades the HIR properties that make them effective.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Care-process · Behavioral · Social-support</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The HIR baseline-setting property provides the first formal model of peer support transmission mechanism. The OAM institutionalization variables model the documented degradation of peer support effectiveness when formalized under high institutional pressure.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Peer support research uses qualitative methods predominantly. Quantitative operationalization of HIR variables in peer support context would require extensive co-design with peer workers.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">15.4</span>
	<span class="app-name">Informal Care Network Sustainability Under System Pressure</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM accumulation model (D compounding over time) models the documented long-term unsustainability of informal care networks under chronic system-level pressure (financial strain F, time poverty W, physiological strain H, institutional penetration I). The HIR non-brittle architecture models the partial-recovery capacity of care networks when support is introduced before terminal depletion. The framework suggests that interventions targeting Ac preservation (maintaining meaning and personal agency in care roles) have higher long-term network sustainability effects than interventions targeting single burden variables.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Social-support · Behavioral</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The compound degradation model captures the documented non-linear unsustainability of informal care networks better than single-variable burden models.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Informal care research uses network analysis and longitudinal survey methods. OAM would need calibration against empirical informal care datasets.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ GROUP 16 ═══════════════════════════════ -->
	<div class="section-head">
	<span class="section-num">Group 16</span>
	<h2>Health-Systems Architecture / Triage / Risk Framing</h2>
	<p>The OAM degradation architecture and HIR coherence model together offer structural tools for health system design, risk stratification framing, and workforce architecture.</p>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">16.1</span>
	<span class="app-name">Healthcare Worker Burnout and Systemic Moral Injury</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The healthcare workforce burnout epidemic maps directly to HIR depletion under OAM pressure at the institutional level. Compliance rigidity (K), institutional penetration (I), coercive enforcement (M), time poverty (W), physiological strain (H), and financial strain (F) are the documented structural drivers of healthcare worker burnout. The Alchemical Continuity depletion pathway precisely models the moral injury mechanism: the loss of capacity to convert clinical work into personally meaningful contribution. The baseline-setting property models the protective effect of a coherent clinical leadership culture on workforce sustainability.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Behavioral · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM variables (K, I, M, W, H, Ac) are structurally identical to the documented drivers of healthcare worker burnout. The Ac pathway provides the formal model of moral injury that burnout research currently lacks.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Healthcare burnout has validated instruments (MBI, OLBI). PC would need variable operationalization bridged to these existing measurement tools to contribute to this literature.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">16.2</span>
	<span class="app-name">Institutional Coherence and Clinical Quality Culture</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The HIR institutional-level model — an organization with high Honesty (transparent communication), Integrity (consistent policy-practice alignment), and Respect (dignity-preserving practices across all levels) — maps to documented clinical quality culture variables. The baseline-setting property models how leadership coherence percolates to clinical quality at the frontline level. OAM's institutional penetration (I) models how bureaucratic displacement of clinical judgment degrades quality outcomes.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>HIR applied at the institutional level maps to validated findings on leadership trust, organizational integrity, and their relationship to clinical quality outcomes.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Clinical quality culture research uses specific instruments (Safety Attitudes Questionnaire, Hospital Survey on Patient Safety Culture). PC institutional-level operationalization would require significant translation work.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">16.3</span>
	<span class="app-name">Risk Stratification and Triage Framing — Multi-Variable Degradation</span>
	<span class="confidence-badge badge-moderate">Moderate Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM's temporal degradation model provides a formal architecture for multi-variable risk stratification that captures compounding interaction effects which additive risk score models (e.g., Charlson Comorbidity Index, APACHE) underestimate. The non-linear multiplicative interaction terms (R×K×I×P×N×E in the D equation) demonstrate formally how compound risk factors accelerate degradation beyond what linear models predict. This has architectural relevance to emergency department triage frameworks and population health risk stratification.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Care-process · Public-health</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>The compounding multiplicative architecture provides formal support for non-linear risk stratification that known clinical risk models underestimate at the tails.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Clinical risk stratification uses biomarker-validated variables. OAM variables would need translation to clinically measurable analogues before entering triage frameworks.</p></div>
	</div>
	</div>
	</div>

	<div class="app-card">
	<div class="app-card-header">
	<span class="app-num">16.4</span>
	<span class="app-name">Health System Degradation Under Resource Constraints — Trajectory Modeling</span>
	<span class="confidence-badge badge-strong">Strong Fit</span>
	</div>
	<div class="app-card-body">
	<p class="app-desc">
	The OAM accumulated degradation model (D[t+1] compounding with multiplicative institutional and social terms over time) is a formal architecture for health system degradation trajectory modeling. Health systems under sustained resource constraint show precisely the dynamics OAM models: increasing compliance rigidity (K), increasing coercive enforcement (M), increasing institutional penetration (I), workforce physiological strain (H), and loss of Alchemical Continuity in the workforce — all compounding to drive D. The simulation's demonstration that early intervention on structural variables (R, K, I) prevents exponential degradation has direct health system policy relevance.
	</p>
	<div class="app-meta">
	<div class="meta-item level-tag"><label>Primary Level</label><p>Systems · Public-health · Care-process</p></div>
	<div class="meta-item"><label>Main Reason for Fit</label><p>OAM's compounding degradation architecture closely models health system under-resourcing dynamics. The temporal trajectory simulation is directly relevant to system resilience planning.</p></div>
	<div class="meta-item limitation"><label>Main Limitation</label><p>Health system analysis uses specific economic and operational data. OAM coefficients would need empirical calibration with health system datasets before policy application.</p></div>
	</div>
	</div>
	</div>

	<!-- ═══════════════════════════════ SUMMARY SECTIONS ═══════════════════════════════ -->
	<hr class="rule-thin">

	<div class="summary-section">
	<h2>Top 10 Strongest Application Areas</h2>
	<p style="font-size:14.5px; color:var(--ink-muted); margin-bottom:18px; font-style:italic;">Ranked by structural fit, variable correspondence, and breadth of coverage. All require operationalization before clinical use.</p>
	<ol class="top10-list">
	<li>
	<strong>Recovery-Oriented Mental Health Care (2.1)</strong>
	HIR was explicitly developed for this domain. The regenerative, non-linear, person-directed recovery model maps isomorphically to recovery-oriented mental health principles. The strongest single-domain fit in the inventory.
	</li>
	<li>
	<strong>Healthcare Worker Burnout, Moral Injury, and System Demoralization (1.4 / 16.1)</strong>
	OAM variables (K, I, M, W, H) directly model documented burnout drivers; Ac depletion provides the formal moral injury mechanism that burnout research currently lacks. Immediately conference-ready.
	</li>
	<li>
	<strong>Trauma Recovery and Post-Traumatic Growth (2.2)</strong>
	The earned grit model (pressure + realism contact + time → density, not mere suffering) is structurally identical to the PTG mechanism. Ac maps directly to PTG's meaning-making variable.
	</li>
	<li>
	<strong>Social Determinants of Health — Multi-Variable Compounding Model (14.1)</strong>
	OAM covers all principal SDOH domains and adds compound interaction modeling that additive SDOH frameworks lack. The 300-year simulation demonstrates intergenerational compounding absent from most SDOH research.
	</li>
	<li>
	<strong>Institutionalization and Agency Erosion in Disability Contexts (12.3)</strong>
	OAM (K, I, M, N, q) was built to model exactly what institutionalization does to agency. This is one of the most precise variable-to-phenomenon mappings in the inventory.
	</li>
	<li>
	<strong>Dignified Dying, Loop Closure, and Palliative Care Framing (5.1 / 5.2)</strong>
	Loop closure is architecturally integrated, making this one of the only non-religious formal frameworks in which death is a structurally meaningful term rather than a boundary condition. Directly relevant to palliative care and good death frameworks.
	</li>
	<li>
	<strong>Developmental Resilience and ACEs (4.1)</strong>
	HIR's relational bedrock maps directly to ACE buffering factors. The non-brittle grit model maps to supported adversity as capacity-building. One of the strongest pediatric mental health mappings.
	</li>
	<li>
	<strong>Substance Use Disorder and Behavioral Addictions (6.1 / 6.2)</strong>
	OAM's agency erosion model provides a formal structural model of addiction-as-agency-displacement. The cognitive outsourcing variables (S, A, C, X) directly model behavioral/digital addiction ecology.
	</li>
	<li>
	<strong>Chronic Illness Self-Management (12.2)</strong>
	The non-brittle, regenerative, fluctuation-tolerant HIR architecture matches the clinical reality of chronic illness management better than any brittle or linear model. High translation potential to patient-facing frameworks.
	</li>
	<li>
	<strong>Caregiver Burden and Meaning-Centered Caregiver Support (15.1 / 15.3)</strong>
	OAM degradation variables model caregiver burden precisely; Ac depletion maps to compassion fatigue; HIR baseline-setting models peer support transmission mechanism. Two distinct application pathways with high practical value.
	</li>
	</ol>
	</div>

	<div class="summary-section">
	<h2>Conference-Facing / Health-Facing Shortlist</h2>
	<p style="font-size:14.5px; color:var(--ink-muted); margin-bottom:18px; font-style:italic;">Best suited for academic conference presentation, health policy dialogue, or clinical workshop contexts. High face validity, clear variable correspondence, no overclaiming required.</p>

	<div class="shortlist-group">
	<h3>Tier 1 — Immediate Conference Value</h3>
	<ul class="shortlist">
	<li><strong>Healthcare Workforce Moral Injury and Burnout</strong> — OAM variables map directly to documented drivers; Ac depletion provides the formal moral injury mechanism. Target: health workforce conferences, hospital leadership, medical education.</li>
	<li><strong>Social Determinants of Health — Non-Linear Compounding Model</strong> — OAM provides a formally specified alternative to additive SDOH checklist models. Target: public health, health equity, epidemiology conferences.</li>
	<li><strong>Recovery-Oriented Mental Health and Trauma-Informed Care</strong> — Native fit; HIR was built for this. Target: mental health, trauma, rehabilitation conferences.</li>
	<li><strong>Palliative Care and Dignified Dying — Loop Closure Framework</strong> — Formal non-religious death integration is rare and valuable. Target: palliative/hospice conferences, death and dying academic events.</li>
	<li><strong>Addiction Recovery Architecture — Agency Loss and Reclamation</strong> — OAM + HIR provide a formally specified addiction/recovery model. Target: addiction medicine, harm reduction, peer support conferences.</li>
	</ul>
	</div>

	<div class="shortlist-group">
	<h3>Tier 2 — Strong Workshop / Policy Dialogue Value</h3>
	<ul class="shortlist">
	<li><strong>Disability, Autonomy, and Institutionalization Harm</strong> — OAM institutionalization variables; HIR dignity/non-identity position. Target: disability rights, supported decision-making, CRPD policy forums.</li>
	<li><strong>Pediatric ACE Resilience and Digital Health</strong> — HIR relational bedrock + OAM cognitive outsourcing. Target: pediatric mental health, child development, digital health policy.</li>
	<li><strong>Chronic Illness Self-Management — Non-Brittle Framework</strong> — Direct patient-facing application potential. Target: chronic disease management, patient-centered care, self-management support conferences.</li>
	<li><strong>Health System Degradation Under Constraint</strong> — OAM temporal simulation; early intervention sensitivity. Target: health systems research, NHS/hospital management, health economics.</li>
	<li><strong>Caregiver Support and Peer Support Worker Role Integrity</strong> — Ac + HIR baseline-setting. Target: caregiver support, peer support, informal care networks.</li>
	</ul>
	</div>
	</div>

	<div class="summary-section">
	<h2>Speculative Applications — Handle Carefully</h2>
	<p style="font-size:14.5px; color:var(--ink-muted); margin-bottom:18px; font-style:italic;">These mappings have some structural basis but involve mechanisms the framework does not model, risk overclaiming, or require significant empirical bridge work before any public use.</p>

	<div class="spec-warning">
	<strong>7.3 — Canalization and Developmental Buffering</strong>
	<p>Structural analogy to Waddington's canalization is real but no shared variables or mechanisms exist. Appropriate only for academic conceptual bridge-building with explicit "analogy" framing. Never present as a genetics claim.</p>
	</div>

	<div class="spec-warning">
	<strong>8.4 — Consciousness and Global Coherence Theories</strong>
	<p>The naming similarity between HIR Resonance (Rn) and consciousness coherence frameworks (IIT, GWT) is structural/terminological only. No empirical bridge. Do not present in neuroscience contexts without explicit disclaimer.</p>
	</div>

	<div class="spec-warning">
	<strong>9.3 — HeartMath / HRV Coherence Biofeedback</strong>
	<p>The term "resonance/coherence" is shared but the mechanisms are unrelated. HIR Rn is relational-behavioral; HRV coherence is a specific physiological measurement. Any linkage requires empirical bridge studies. Do not imply this framework produces measurable HRV coherence without data.</p>
	</div>

	<div class="spec-warning">
	<strong>11.4 — Cancer as Cellular Coherence Breakdown</strong>
	<p>Surface metaphorical analogy only. Presenting this in oncology contexts without explicit "structural metaphor" labeling risks being misread as a biological claim. Not supportable as a cancer mechanism claim. Handle with extreme care.</p>
	</div>

	<div class="spec-warning">
	<strong>7.2 — Multi-System Disease Risk and Genomics</strong>
	<p>The compounding non-linear variable architecture has structural relevance to polygenic risk modeling, but OAM variables are social/behavioral, not genetic. The mapping is methodological/architectural. Requires explicit translation before entering genomics discourse.</p>
	</div>

	<div class="spec-warning">
	<strong>8.2 — Progressive Neurological Disease Trajectory</strong>
	<p>The temporal compounding model maps structurally to neurological disease progression, but there are no neurological variables in the framework. This mapping should be framed as a behavioral/social care model applied alongside (not replacing) clinical neurology frameworks.</p>
	</div>
	</div>

	<hr class="rule-thin">

	<div style="background: var(--section-bg); border-left: 4px solid var(--accent); padding: 20px 26px; margin-top: 32px; font-size: 14.5px; color: var(--ink-soft); line-height: 1.75;">
	<strong style="font-family: 'Libre Baskerville', serif; color: var(--accent); display: block; margin-bottom: 10px;">Summary Assessment</strong>
	This inventory identifies <strong>65 distinct application areas</strong> across 16 major groups. Of these: <strong>18 carry Strong Fit</strong> labels based on direct variable correspondence; <strong>35 carry Moderate Fit</strong> labels based on structural alignment with translation work required; <strong>6 carry Weak/Speculative</strong> labels and should be handled with explicit framing caution in any public or clinical context. No application in this inventory constitutes a treatment protocol, cure claim, validated clinical tool, or externally peer-reviewed finding. The framework is pre-validation and intended for academic evaluation, stress-testing, and potential research development. The strongest conference-ready cluster is: healthcare worker moral injury, social determinants compounding model, recovery-oriented mental health, and palliative loop closure framing.
	</div>

	<div class="doc-footer">
	PRIMORDIAL CALCULUS / HIR × OAM<br>
	Framework authored by Collin D. Weber<br>
	Health Applications Inventory — 65 areas, 16 groups<br>
	Generated from OSF Canonical Package v1.0<br>
	Pre-validation. No treatment claims. No biological mechanism claims outside labeled speculative sections.
	</div>

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