Graph dimensions: 120 nodes, 472 associations, 10 hub nodes above 19 connections
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1. Political capture functions as a closed loop, not merely an obstacle.
`Healthcare Industry Political Capture` (44 connections, w=7.5) has bidirectional edges with nearly every major cost-inflating mechanism. It does not simply block reform — it is enabled by the same mechanisms it enables. `Hospital Market Power Consolidation` --[enables]--> `Healthcare Industry Political Capture` and `Healthcare Industry Political Capture` --[enables]--> `Hospital Market Power Consolidation`. `AMA RUC Specialist Pricing Capture` --[enables]--> `Healthcare Industry Political Capture`; `Healthcare Industry Political Capture` maintains the GME cap that amplifies AMA bargaining power. This circularity means the capture node is structurally load-bearing: it is both cause and effect of the system's cost architecture.
2. Multi-payer fragmentation is the structural multiplier, not merely one pathology among many.
`US Multi-Payer Healthcare Fragmentation` (27 connections, w=8.5) is the source node for `Healthcare Administrative Cost Overhead`, `Health Insurance Adverse Selection Death Spiral`, `HITECH EHR Administrative Overhead Paradox`, `Medical Error Iatrogenesis Fragmentation Cost`, and `Prevention ROI Insurance Temporal Mismatch`. None of these five downstream nodes exist without fragmentation as a precondition. Fragmentation is also a prerequisite for `PBM Rebate Trap Drug Pricing Inflation` --[enabled_by]--> fragmentation, and for `Medicare Advantage Risk Score Gaming` --[exploits]--> fragmentation. The graph represents fragmentation as an amplifier of every major cost mechanism rather than one cost mechanism among many.
3. Physician supply is constrained from two independent directions simultaneously.
The graph contains at least six distinct nodes describing the GME/BBA 1997 physician supply cap (GME Cap Physician Supply Constraint, ACGME Residency Cap Physician Scarcity, GME Residency Slot Medicare Cap, GME Residency Cap Physician Supply Bottleneck, GME Residency Slot BBA 1997 Physician Supply Cap, GME Medicare Funding Freeze Physician Supply Chokepoint) and at least three nodes describing scope-of-practice restrictions (NP/PA Scope of Practice Physician Monopoly, Scope of Practice Suppression Physician Supply Cartel, NP Scope of Practice Restriction). Both constraint mechanisms have independent edges to `AMA RUC Specialist Pricing Capture`, suggesting supply restriction and price-setting capture operate as a coordinated system rather than separate phenomena.
4. The 340B program appears six times as distinct nodes.
340B Drug Pricing Hospital Capture, 340B Drug Discount Cross-Subsidy Capture, 340B Drug Discount Program Hospital Capture, 340B Drug Program Distortion, 340B Drug Program Profit Capture, and 340B Drug Program Safety Net Capture represent one federal program analyzed from six distinct angles. Across these nodes, the program has outbound edges to `Hospital Market Power Consolidation` (funded_by, funds, incentivizes, amplifies), `Pharma Patent Thicket FDA Exclusivity Stack` (amplifies, forces_higher_prices_on), and `Nonprofit Hospital Tax-Exempt Charity Care Gap` (laundered_as). The graph treats 340B as both a cost-inflating mechanism and a reform-capture exemplar.
5. Weight disparity identifies incomplete graph regions.
Eleven nodes carry weight=1 despite having significant connection counts: `Pay-As-You-Go Healthcare Finance Collapse` (26 connections), `Healthcare Worker Double Bind` (23 connections), `PE Healthcare Rollup Stealth Consolidation` (high connectivity), and others. The same concepts appear as duplicate nodes with different weights — `1990s HMO Backlash Managed Care Collapse` (event, w=7.5) and (idea, w=1); `ACA Subsidy Cliff Coverage Erosion 2026` (event, w=7.5) and (idea, w=1); `Medicare HI Trust Fund OBBB Solvency Collapse` (event, w=8.5) and (idea, w=1). These duplicates indicate a data merge artifact. The w=1 versions are likely stubs from an earlier graph that were not fully integrated or resolved against their higher-weight counterparts.
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Loop 1: Political Capture ↔ Hospital Consolidation (direct mutual reinforcement)
`Hospital Market Power Consolidation` --[enables, w=8]--> `Healthcare Industry Political Capture` --[enables, w=8]--> `Hospital Market Power Consolidation`
Two-node bidirectional loop. This is the shortest feedback loop in the graph and the tightest mutual reinforcement structure identified.
Loop 2: AMA Pricing → Supply Scarcity → AMA Bargaining Power (3-node)
`AMA RUC Specialist Pricing Capture` --[causes]--> `US Medical Education Debt Specialty Distortion` --[amplifies]--> `AMA RUC Specialist Pricing Capture`
Simultaneously: `AMA RUC Specialist Pricing Capture` --[causes]--> `Primary Care Desert` --[amplifies]--> `Fee-for-Service Volume Incentive` --[amplifies]--> `AMA RUC Specialist Pricing Capture`
The AMA node is both origin and terminus of specialty-distortion pathways.
Loop 3: Fee-for-Service → Consolidation → Capture → FFS (4-node)
`Fee-for-Service Volume Incentive` --[enables, w=6]--> `Hospital Market Power Consolidation` --[enables, w=8]--> `Healthcare Industry Political Capture` --[maintains FFS by constraining reform]--> `1990s HMO Backlash Managed Care Collapse` --[reinforced, w=8]--> `Fee-for-Service Volume Incentive`
The HMO backlash node functions as the historical mechanism by which political capture previously restored FFS after managed care cost controls.
Loop 4: OBBB → Coverage Loss → Outcomes → Fiscal Pressure → OBBB (4-node)
`Pay-As-You-Go Healthcare Finance Collapse` --[triggered]--> `OBBB Medicaid Defunding 2025` --[amplifies]--> `Medical Debt Consumer Harm Endpoint` --[causes]--> `US Healthcare Outcomes Paradox` --[accelerates]--> `Pay-As-You-Go Healthcare Finance Collapse`
The OBBB event is simultaneously caused by fiscal collapse and accelerates further fiscal collapse through coverage loss and worsened outcomes.
Loop 5: Prior Authorization → Burnout → Shortage → Prior Auth Leverage (4-node)
`Prior Authorization Insurer Gatekeeping` --[amplifies]--> `Physician Moral Injury PE Burnout Shortage Feedback` --[amplifies]--> `Rural Hospital Closure Crisis` → diminished care supply → increased insurer market leverage. The burnout node also connects back: `Prior Authorization Insurer Gatekeeping` --[amplifies, w=9]--> `Physician Moral Injury PE Burnout Shortage Feedback` --[amplifies, w=7]--> `Rural Hospital Closure Crisis` --[worsens]--> `US Healthcare Outcomes Paradox` --[used to justify alternative payment models that further concentrate insurer control].
Loop 6: MLR Regulation → Cost Inflation → MLR Profit → Cost Inflation (indirect)
`Chargemaster Price Opacity Theater` --[amplifies, w=8]--> `MLR Perverse Incentive Profit Scales With Spending` --[amplifies, w=8]--> `US Multi-Payer Healthcare Fragmentation` --[enables]--> `Chargemaster Price Fiction`/opacity. Higher spending makes MLR-compliant insurers more profitable, which reduces incentive to control costs that generate the opacity that enables further spending.
Loop 7: GLP-1 Fiscal Pressure → OBBB → Coverage Loss → Obesity Load → GLP-1 Demand
`GLP-1 Medicare PAYG Double Bind` --[fiscal_pressure_driving, w=7]--> `OBBB Medicaid Defunding 2025` --[reduces Medicaid obesity treatment coverage] → `Obesity Epidemic US Healthcare Cost Multiplier` grows unchecked → `GLP-1 Medicare PAYG Double Bind` demand increases. The fiscal pressure driving coverage cuts amplifies the underlying condition driving fiscal pressure.
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1. ERISA preemption is both the primary reform blocker and the vehicle for the primary market-based workaround.
`ERISA Preemption State Reform Firewall` --[prevents_solution_to]--> `It's Prices Not Utilization` (w=9) and `ERISA Preemption State Reform Firewall` --[blocks_key_mechanism_of]--> `US Healthcare Reform Necessary Conditions` (w=9). Simultaneously, `Direct-to-Employer Healthcare Bypass` --[exploits_same_power_as]--> `ERISA Preemption State Reform Firewall` (w=9). The same federal preemption authority that prevents state single-payer or all-payer rate-setting also gives large self-insured employers the power to bypass state insurance mandates. The structural source of the problem and the available market workaround are the same legal provision.
2. The MLR consumer protection rule creates a perverse incentive that the largest insurer exploits.
`MLR Perverse Incentive Profit Scales With Spending` --[exploited_by]--> `UnitedHealth Optum Vertical Integration Flywheel` (w=9). The Medical Loss Ratio rule (requiring insurers to spend ≥80-85% of premiums on care) was designed to constrain insurer profit. Because absolute profit scales with total spending at a fixed ratio, the rule creates an incentive to maximize spending rather than control it. This is a non-obvious structural consequence of ratio-based regulation applied to a cost-inflating system.
3. A government safety-net discount program directly funds hospital market consolidation.
`340B Drug Discount Program Hospital Capture` --[funds, w=8]--> `Hospital Market Power Consolidation`. The 340B program grants hospitals deep drug discounts; hospitals capture the spread between acquisition cost and reimbursement as margin. This margin directly funds acquisitions, enabling the consolidation that is itself a primary driver of price increases. The safety-net program's output is the opposite of its stated purpose.
4. HITECH's $38B EHR investment increased administrative burden by colliding with multi-payer complexity.
`HITECH EHR Administrative Overhead Paradox` --[caused_by, w=9]--> `US Multi-Payer Healthcare Fragmentation`. The $38B investment in electronic health records was predicated on interoperability and efficiency gains; those gains were negated because the multi-payer billing environment generated heterogeneous documentation requirements that EHR systems were then required to serve. The technology amplified the underlying fragmentation's administrative load rather than reducing it.
5. The physician supply cap creates labor dependency on foreign-trained physicians, introducing immigration policy as a healthcare variable.
`GME Residency Slot Medicare Cap` --[undermines_via_IMG_dependency]--> `Labor Cost Arbitrage` and `IMG Physician Dependency 2026 Visa Crisis` --[compounded_by]--> `OBBB Medicaid Defunding 2025`. The cap on residency slots made US hospitals structurally dependent on International Medical Graduate physicians, who often practice in underserved areas under visa conditions (J-1 waivers). Immigration policy changes (2026 context) become a direct determinant of rural healthcare access, a linkage not present in conventional healthcare reform analysis.
6. Direct-to-employer bypass reduces coalition pressure for systemic reform.
`Direct-to-Employer Healthcare Bypass` --[undermines_coalition_for_countering, w=7]--> `Healthcare Industry Political Capture`. Large employers achieving cost relief through direct contracting exit the political coalition that would otherwise advocate for structural reform. This is the mechanism by which successful partial workarounds may reduce aggregate reform pressure while leaving the system's underlying architecture unchanged.
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Healthcare Industry Political Capture (44 connections, w=7.5)
This node has more edges than any other in the graph. Its outbound edges enable: `Hospital Market Power Consolidation`, `Pharma Patent Thicket FDA Exclusivity Stack`, `US Multi-Payer Healthcare Fragmentation`, `CON Laws Hospital Monopoly Shield`, `NP/PA Scope of Practice Physician Monopoly`, `Mental Health Parity MHPAEA Enforcement Gap`, `GME Residency Slot Bottleneck`, `Medicare Advantage Risk Score Gaming`, `ERISA Preemption State Reform Block` (maintenance), `Certificate of Need Hospital Market Protection`, `Medicaid Managed Care MCO Privatization` (entrenched), and the `340B Drug Program Profit Capture` (protected). Its inbound edges come from: `AMA RUC Specialist Pricing Capture`, `Hospital Market Power Consolidation`, `UnitedHealth Optum Vertical Integration Flywheel`, `Certificate of Need Supply Restriction`, `MLR Perverse Incentive Profit Scales With Spending`, `Healthcare Industry Political Capture` is also listed as constraining `IRA Medicare Drug Price Negotiation` (w=9) and blocking `US Healthcare Reform Necessary Conditions` (w=9). The node functions structurally as a bidirectional relay: it amplifies mechanisms that increase its own resource base and blocks mechanisms that would reduce that resource base.
Hospital Market Power Consolidation (38 connections, w=7.5)
The second-highest-connectivity node and the mechanism most directly linking financial consolidation to price behavior. Key outbound edges: enables `Healthcare Industry Political Capture`, exploits `Chargemaster Price Fiction`, generates `Medical Debt Financial Toxicity`, undermines `ACO Value-Based Care Structural Ceiling`, undermines `Hospital Price Transparency Rule Failure`. Key inbound edges: accelerated by `PE Healthcare Rollup Stealth Consolidation`, `Certificate of Need Laws`, `340B Drug Discount Program`, `CON Laws`, `Chargemaster Price Opacity Theater`, and fee-for-service incentives. The node is the convergence point for supply-side competitive mechanisms (CON laws, PE rollups) and demand-side payment mechanisms (FFS, chargemaster).
US Multi-Payer Healthcare Fragmentation (27 connections, w=8.5)
Highest node weight among the hub cluster (8.5). Acts as a structural precondition rather than a downstream consequence — it is the source of administrative overhead, adverse selection dynamics, HITECH's failure, and medical error costs. It is maintained by ERISA preemption and ESI tax exclusion, and is countered by the Maryland model, Germany's GKV system, and Taiwan's NHI transition. The graph positions this node as the foundational architectural feature from which multiple cost mechanisms emerge; it is not primarily caused by other nodes in the graph but by historical policy choices (ESI wartime wage controls, ERISA 1974) represented upstream.
Fee-for-Service Volume Incentive (24 connections, w=8)
The payment architecture node. Amplified by: ESI tax exclusion, Medicare rate benchmark spillover, primary care desert, defensive medicine, AMA RUC pricing, and medical arms race diffusion. Its most structurally significant feature is that it is the mechanism blocked by ACO value-based care reforms — and that blockage is described as constrained by the 1990s HMO backlash. Every major reform mechanism in the graph that does not address FFS directly (Maryland model, Germany model, Taiwan model) is described as countering it indirectly through rate-setting.
It's Prices Not Utilization (23 connections, w=9)
The highest weight among the top-10 hub nodes (w=9) and the central empirical claim of the graph. This node serves as the thesis that multiple mechanisms prove, multiple mechanisms explain, and multiple barriers prevent addressing. Inbound edges proving it: `Hospital Market Power Consolidation`, `AMA RUC Specialist Pricing Capture`, `GME Cap Physician Supply Constraint`, `ACGME Residency Cap Physician Scarcity`, `Medical Tourism Arbitrage Escape Valve`, `Germany GKV-AMNOG Regulated Multi-Payer Model`, `Hospital Chargemaster Price Anchor`. Outbound edges blocked by: `ERISA Preemption State Reform Firewall` --[prevents_solution_to]--> `It's Prices Not Utilization`. The node is structurally the graph's central proposition: everything else either demonstrates, amplifies, or prevents addressing it.
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1. The ERISA paradox creates competing implications for reform strategy.
`ERISA Preemption State Reform Firewall` simultaneously blocks state-level reform (via its state reform firewall function) and enables the only proven market-based workaround (`Direct-to-Employer Healthcare Bypass`). The graph does not resolve whether the employer bypass reduces net harm (by delivering cost relief to covered populations) or increases net harm (by reducing political pressure for structural change via `undermines_coalition_for_countering`). Both associations carry weights of 8-9, indicating equal structural significance without directional resolution.
2. The GLP-1 fork has binary outcomes with opposite systemic effects.
`GLP-1 Medicare Coverage Political Impasse` --[triggers]--> `Morbidity Expansion vs Compression Fork`. If GLP-1 drugs are covered broadly and reduce obesity prevalence (compression), they reduce the `Obesity Epidemic US Healthcare Cost Multiplier` and improve Medicare fiscal trajectory. If not covered (or covered inadequately), morbidity expands, worsening `Pay-As-You-Go Healthcare Finance Collapse`. Simultaneously, coverage creates near-term fiscal pressure (`GLP-1 Medicare PAYG Double Bind`) that may trigger further coverage cuts (`OBBB Medicaid Defunding 2025`). The graph has no mechanism for resolving which trajectory occurs — this is presented as an open fork with major downstream effects on at least seven other nodes.
3. CON laws are described with a dual role that is directionally ambiguous.
`CON Law Incumbent Supply Cartel` --[has_dual_role_in, w=5]--> `Rural Hospital Closure Crisis`. The edge weight (5) is the lowest non-co_activated weight in the graph, and the label `has_dual_role` is not directional. CON laws both protect incumbent hospitals from competition (which could prevent closure) and prevent efficient competitors from entering (which could accelerate closure of inefficient incumbents). The graph identifies this tension but does not resolve the net directional effect.
4. IRA drug price negotiation is simultaneously a reform success and a threatened mechanism.
`IRA Medicare Drug Price Negotiation` --[counters, w=8]--> `Pharma Patent Thicket FDA Exclusivity Stack`; `IRA Medicare Drug Price Negotiation` --[constrained_by, w=9]--> `Healthcare Industry Political Capture`; `PBM Rebate Trap Drug Pricing Inflation` --[undermines, w=7]--> `IRA Medicare Drug Price Negotiation`; `Pharmaceutical Patent Thicket Evergreening` --[undermines, w=7]--> `IRA Medicare Drug Price Negotiation`. The IRA is the only inbound reform edge to the pharma patent thicket node, but it faces undermining from two directions simultaneously (PBM rebate dynamics and patent evergreening) plus constraint from political capture. The graph indicates reform exists but is structurally outflanked.
5. The weight=1 hub nodes represent an unresolved analytical gap.
`Pay-As-You-Go Healthcare Finance Collapse` (26 connections) and `Healthcare Worker Double Bind` (23 connections) are among the most connected nodes in the graph but carry weights of 1, contradicting the convention that weight reflects structural importance. These nodes appear in many high-weight associations (w=8-9) as both sources and targets, suggesting they are analytically significant but incompletely characterized. Whether the weight=1 reflects analytical uncertainty, data import artifacts (duplicate node conflict), or intentional placeholder status is not resolvable from the graph data alone.
6. Physician supply constraint redundancy obscures net leverage.
Six GME-related nodes and three scope-of-practice nodes describe overlapping phenomena. Their associations to hub nodes sometimes appear as distinct causal pathways (e.g., both `GME Residency Slot Medicare Cap` and `ACGME Residency Cap Physician Scarcity` have independent edges to `AMA RUC Specialist Pricing Capture`) but may represent the same causal mechanism analyzed redundantly. The graph does not indicate whether eliminating the GME cap alone would be sufficient or whether scope-of-practice reform is independently necessary. The structural leverage of each cannot be isolated.
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H1: Political capture is the single highest-leverage intervention point, and its removal would produce non-linear effects.
The graph assigns 44 connections to `Healthcare Industry Political Capture`, with its outbound edges enabling nearly every listed cost mechanism and its inbound edges sustained by those same mechanisms. If political capture were reduced, the graph predicts simultaneous weakening of: CON laws, NP/PA practice restrictions, GME cap maintenance, ERISA firewall maintenance, pharma patent protection, and MA risk-score gaming. *Testable prediction:* states with lower healthcare-sector lobbying intensity should show greater correlation between hospital market concentration measures and regulatory response (e.g., certificate-of-need reform, price transparency enforcement). If no correlation exists, the political capture node's weight overstates its causal role.
H2: The employer bypass pathway creates a bifurcated cost trajectory between large and small employer markets.
`Direct-to-Employer Healthcare Bypass` --[partially_circumvents]--> `PBM Rebate Trap Drug Pricing Inflation` and --[undermines_coalition_for_countering]--> `Healthcare Industry Political Capture`. If large self-insured employers systematically reduce their healthcare costs via direct contracting and reference-based pricing, the distribution of cost-shift burden would concentrate in small employer, individual market, and Medicaid populations. *Testable prediction:* premium trends in large-group markets (>1,000 employees) should diverge from small-group and individual market trends over 2018-2028, controlling for benefit design changes.
H3: The GME cap-AMA feedback loop is a higher-leverage intervention than any single pricing reform.
The graph shows `GME Cap Physician Supply Constraint` --[amplifies_bargaining_power_of]--> `AMA RUC Specialist Pricing Capture` and `GME Residency Slot Medicare Cap` --[sustains]--> `AMA RUC Specialist Pricing Capture`. If physician supply were substantially increased (GME cap lifted, scope-of-practice restrictions removed), the supply-side basis for specialist pricing power would diminish, reducing the AMA's RUC capture function without requiring direct price regulation. *Testable prediction:* states that have expanded NP/PA scope of practice should show measurable decreases in specialist price premiums (relative to Medicare rates) in the five years following scope expansion, controlling for market concentration.
H4: The Maryland all-payer model's apparent effectiveness is an artifact of its unique legal status rather than a replicable model.
`Maryland All-Payer Rate Setting Model` --[counters, w=9]--> `US Multi-Payer Healthcare Fragmentation`; `ERISA Preemption State Reform Firewall` --[limits_scope_of]--> `Maryland All-Payer Rate Setting Model`. Maryland's model functions under a unique federal waiver from Medicare/Medicaid price regulations that no other state has replicated. *Testable prediction:* if the graph's structural diagnosis is correct (ERISA and fragmentation as blocking mechanisms), states that attempt Maryland-style rate-setting without federal waivers should fail within 5 years due to employer self-insurance carve-outs. Historical cases (Massachusetts, Vermont) should show this pattern.
H5: AI-assisted prior authorization creates an escalating information-asymmetry arms race with predictable phases.
`AI Prior Authorization Denial Arms Race` --[mirrors_information_asymmetry_of]--> `Medicare Advantage Risk Score Gaming`. Both mechanisms are described as information asymmetry games — MA plans game risk scores upward; insurers game denial rates upward via AI. *Testable prediction:* denial rates should have increased at a non-linear rate beginning approximately 2021-2023 (AI adoption) and appeals volumes should begin increasing with a 12-24 month lag as provider-side AI tools deploy. A further prediction: insurer profit margins from prior auth denial should be measurable as a distinct line item in MLR calculations, and those margins should correlate with AI investment levels.
H6: The OBBB's compound effects will be observable as a measurable discontinuity in rural hospital closure rates.
`OBBB Medicaid Defunding 2025` has nine outbound edges rated w=7-9.8, targeting `Rural Hospital Closure Crisis`, `Medical Debt Consumer Harm Endpoint`, `Medical Debt Financial Toxicity`, `Pay-As-You-Go Healthcare Finance Collapse`, `Mental Health Parity MHPAEA Enforcement Gap`, `Medicaid Coverage Gap NFIB Sebelius Fracture`, `Medicare HI Trust Fund OBBB Solvency Collapse`, `IMG Physician Dependency 2026 Visa Crisis`, and `Health Insurance Adverse Selection Death Spiral`. *Testable prediction:* rural hospital closure announcements in non-expansion states should show a statistically significant acceleration beginning Q3 2025 relative to the 2018-2024 baseline rate (pre-OBBB). If the compound effects are real, the closure rate should exceed models based on pre-OBBB Medicaid coverage trends alone.
H7: The morbidity fork is the highest-uncertainty variable in the system's long-run fiscal trajectory.
`Morbidity Expansion vs Compression Fork` has outbound edges determining the trajectory of `Obesity Epidemic US Healthcare Cost Multiplier`, `US Healthcare Outcomes Paradox`, `End-of-Life Care Fee-for-Service Over-Treatment`, `Pay-As-You-Go Healthcare Finance Collapse`, `GLP-1 Medicare PAYG Double Bind`, and `Social Determinants Healthcare Spending Substitution`. The resolution of this fork depends on a politically blocked coverage decision (GLP-1 Medicare coverage). *Testable prediction:* long-run Medicare actuarial projections produced before and after any GLP-1 coverage decision should show a non-linear divergence in the 2035-2045 cost trajectory, with the magnitude of divergence being larger than any other single policy variable in the model.
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*Note on data quality: The graph contains duplicate nodes for at least four concepts (1990s HMO Backlash, ACA Subsidy Cliff, Medicare HI Trust Fund Solvency, Pay-As-You-Go Finance Collapse), each appearing as both an event node with high weight and an idea node with weight=1. Associations may be split between these duplicates. Analysis above treats the high-weight event versions as authoritative where duplication exists.*