Methodology

Canonical parameters

Every parameter displayed on this site originates in one of two canonical sources: the canonical parameters document (published in full at /canonical-parameters, v10.2 current canon) and the fiscal workbook (NAA_Fiscal_Projection_v10.xlsx, 18 tabs, 1,745 formulas). When sources disagree, the workbook wins. Every AI-assisted response carries a version footer (— Based on NAA DNA v10.2) so drift between site canon and AI responses can be detected.

Lock note. Prior documents — including DNA v17, v19, v20, v21 drafts — are superseded. They remain on file as architectural-exploration archives only. See /canonical-parameters →.

Three scenarios

The fiscal engine simulates three scenarios, distinguished primarily by the Distributed Healthcare cost basis. Public-facing materials lead with the conservative basis; the $5.55T target is labeled aspirational per v10.2 directive:

• Optimistic (aspirational): Distributed Healthcare basis $5,550B. Assumes 25% admin savings and drug pricing held at 120% OECD median for 15 years. Debt Sunset triggers downward. Retirement ~2052.
• Central: Distributed Healthcare basis $5,900B. Debt Sunset mostly at baseline. Retirement ~2079 (Year 50, counting 2030 as Year 1). Year-10 deployable surplus ~$0.79T.
• Conservative (public-lead basis): Distributed Healthcare basis $6,250B. Most defensible for CBO-style scoring. Debt Sunset triggers upward. Retirement held inside the 50-year corridor.

In every scenario, federal debt retires within 50 years by architectural construction (2030 Year 1 through 2079 Year 50). What varies is the payroll tax and top-rate path the Debt Sunset Governor follows to get there.

Known sensitivities (published; pending calibration)

• Wealth & institutional excise erosion: European experience shows 30–40% behavioral erosion of estate-prepayment bases within five years via valuation disputes and mobility. The conservative scenario will apply a 35% haircut in the next model revision (central and optimistic keep the current assumption pending empirical data).
• VAT base vs. Pre-bate cost: Pre-bate of ~$290/adult/month at 10% VAT scales to ~$400B/year. Gross VAT near $2.1T implies a consumption base that requires validation against CBO 2039 projections; the central scenario may need to move to a 10% standard rate from the current 9%.
• Carbon revenue decay: The fee escalator tops out at $680/ton and emissions fall over the horizon. By the late 2040s, carbon receipts fund the Energy Stipend and little else. Carbon money is not used to backfill permanent spending — the surplus through the 2030s accrues to the Climate Adaptation Trust, not the General Fund.
• Interest-rate path: Chapter 4 uses a payroll tax corridor but does not yet publish the rate path. If rates stay higher for longer, central retirement slips 6–8 years. The full path and debt-retirement sensitivity band are staged for the next publication.

Dynamic-scoring aspiration

CBO pre-scoring is being pursued through three external channels: the Penn-Wharton Budget Model (PWBM), Resources for the Future (RFF) for carbon and externality components, and the Brookings Hamilton Project for distributional analysis. Until dynamic scoring is complete, certain revenue lines — Alliance Incentive tariff revenue in particular — are displayed as sensitivity bands rather than point estimates.

What is not yet scored

• Alliance Incentive tariff revenue ($40–120B/year band pending dynamic scoring)
• Specific state-level rollout schedules
• Bottleneck Workforce Programs envelope
• Several externality rates pending EPA cost-benefit review
• Behavioral elasticity for household carbon response (ε = 20–80% band, see Climate tab)

Sensitivity bands vs. point estimates

Every numeric claim on the site carries one of five labels:

• [ARCHITECTURAL] — architectural commitment, not a point estimate (e.g., debt retires within 50 years; central ~2079)
• [POINT] — canonical point estimate from DNA v10.3 (payroll tax 28%, Universal Child Allowance beginning at $800/mo, carbon fee $80/ton Year 1)
• [BAND] — central estimate within a published range (Alliance Incentive $40–120B at maturity)
• [PLACEHOLDER] — awaits CBO / EPA / National Statistics Board scoring
• [HISTORICAL] — based on a specific historical datum (CBO 2025 LTBO, NHE 2024)

Two composite scores: an empirical architecture, not a claim

COMPASS splits quality-of-life measurement into two composite scores because they are hypothesized to respond to different remedy types at different speeds. Individual scores measure outcomes that travel with people — health, education, income, victimization. Place-based scores measure structural conditions of the tract — infrastructure proximity, housing stock, environmental exposure, local crime rate. A third Balanced composite is the geometric mean across all eight domains, preserved for continuity.

The split is a litmus test for action guidance. If a tract's individual score is low but its place-based score is moderate, remedies that deliver cash and services to individuals (Universal Child Allowance, Pre-bate, Skills Wallet, SUD treatment) are expected to lift that score faster. If place-based score is low but individual score is moderate, remedies that build infrastructure (FQHC construction, mobile health, broadband, school investment) are expected to lift faster.

This architecture is validated only to the extent that the two scores do diverge, and that different remedies actually produce the predicted differential lifts. Quarterly regeneration publishes the measurements; annual analysis (starting Year 2) tests whether elasticity coefficients match the two-composite hypothesis. If the composites move in lockstep regardless of remedy type across two years of data, the architecture collapses to a single score and the site simplifies. That conditional commitment is the honest frame.

Elasticity model — first-cut and how it updates

All lift estimates on this site (the fields carrying a gold ⁂) come from a v10.1 first-cut elasticity model derived from pre-launch parameters. Empirical coefficients replace these estimates after the first annual analysis, published Year 2 of deployment. The analysis regresses quarterly score changes on intervention amounts per tract, separately for individual and place-based composites, and publishes the delta between predicted and observed lift per remedy type. The model changelog — date, what changed, and why — lives on this page.

Domain weights (v10.1 first-cut)

Each domain contributes to both composites with different weights; weights sum to 1.0 per domain. Initial values are defensible first-cut estimates and version-stamped as v10.1. Any update is documented on the methodology changelog.

• Health & Longevity: 55 individual / 45 place-based
• Education & Skills: 45 / 55
• Economic Security: 65 / 35
• Housing & Infrastructure: 30 / 70
• Safety & Justice: 40 / 60 (individual-side data is sparse; see note below)
• Environment & Climate: 25 / 75
• Civic Engagement: 55 / 45
• Child & Family Wellbeing: 50 / 50

Safety & Justice data gap

Safety & Justice is the most data-challenged of the eight for this split. Place-based crime data (FBI UCR, state crime registries) is available at tract or small-area resolution. Individual-side crime data (victimization and incarceration by resident) is sparse — NCVS reports regionally, not locally. Tract pages in this domain display a data-quality indicator (🟢 full / 🟡 partial / 🔴 gap). The National Statistics Board roadmap commits to improving individual-side data collection as part of the measurement architecture buildout.

How the two place-based metrics are computed

The Accord displays two tract-level metrics, both pre-computed to the tract centroid and regenerated quarterly. QOL Composite (0–10) collapses the eight COMPASS domains (Health, Education, Economic, Housing, Safety, Environment, Civic, Child/Family — see Ch 15) via geometric mean. Equal domain weighting; geometric mean penalizes weak links so that one catastrophic domain is not masked by a strong one.

Critical Access Proximity (0–10) measures drive-time to six life-threatening-service facility types: Level II+ trauma, OB-GYN, specialty care (cardiology/oncology/neurology), dialysis, mental-health crisis, and FQHC. Each type scored 0–10 against published clinical thresholds (e.g., Level II: 10 at ≤30 min, 0 at ≥120 min). Six sub-scores combined via geometric mean.

Why two, not thirteen. Earlier drafts carried a separate layer per facility type. Two composites communicate the structure better: one tells you what the tract is like to live in, the other tells you what the tract is like to have a heart attack in. Sub-scores remain visible on tract click-through.

Pre-computation is from tract centroid (not county centroid) to the nearest facility point. ~73,000 tracts × 6 facility types ≈ 438,000 distance computations, haversine with urbanicity-adjusted drive-time multipliers. Regenerated quarterly by scripts/proximity_compute.py.

Three-tier delivery model

Healthcare access is delivered through three tiers with different clinical capabilities and deployment ramps. The map reports Critical Access in both Physical (brick-only drive-time) and Effective (best across all available tiers) forms so the distinction is visible.

• Tier 1 · Telehealth (Y1-3, universal). Post Office 2.0 booth at every site. Capital ~$1.55B (50K/booth × 31K sites), operating $155M/yr. No substitute for acute surgery, labor & delivery, or dialysis sessions.
• Tier 2 · Mobile (Y1-5, targeted). Scheduled mobile units for OB-GYN, dialysis, specialty care, crisis response, FQHC circuits. ~$1.1B capital over 5 years; $550M/yr operating at maturity; ~18M residents served.
• Tier 3 · Brick-and-mortar (Y3-20, plausibility-gated). VHA expansion > hospital upgrade > integrated-care anchor > county-seat addition > greenfield. Only tier for 24/7 surgical and inpatient acute care.

Tier capability matrix

Not every facility type can be delivered at every tier. Tele-psychiatry is standard of care (75% of brick value); dialysis via telehealth is clinically impossible (0%). The matrix:

Effective vs physical Critical Access

The map reports both versions. Physical captures time-to-brick-and-mortar — the residual gap Tier 3 must close over 20 years. Effective captures best available time-to-care across whichever tiers are deployed in that tract at that year. For acute trauma, physical is what matters. For mental-health crisis, specialty consult, routine primary care — effective is what matters. Both are published.

Tier 3 plausibility gate + site preference

The 20-year schedule ranks tracts by composite deficit (drive-time excess × log-population × adjacency bonus × access-urgency) and selects each facility's site through the plausibility gate: VHA expansion > hospital upgrade (Critical Access Hospital → Level III → Level II) > integrated-care anchor (Kaiser-model) > county-seat addition > greenfield (only if catchment ≥150K and no upgradable anchor within 60-120 min). Capacity constraints reflect workforce pipelines, not capital — Level II trauma is limited to ~7 new facilities/year by the 5-year-lag surgeon residency pipeline.

Operating subsidy for security capacity. Per Blueprint Ch 20, Level II trauma centers, OB-GYN outreach, specialty care, and mental-health crisis facilities in small catchments receive permanent operating subsidy above fee revenue. Their value is in standing capability, not throughput — like fire stations. This is a permanent line in Distributed Healthcare's budget, not a transition cost.

Red-team process

The document has been red-teamed continuously via structured conversations with multiple AI systems (Claude, ChatGPT). External validator engagement with the institutions listed above is ongoing. When errors are identified, corrections are posted publicly to the updates log with the prior value, the correction, and the source.

Authored by Bill Hersman, LiDAR Space LLC · DNA v10.2 · April 2026