SimOntica Monitor Rupture Index
Live contradiction-debt & institutional-rupture tracking for state governance — a real-world instrument of the SimOntica social ontology.
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Global rupture map

Countries shaded by rupture band · pulsing markers flag emerging events & band changes · click a country to inspect.
Bands are derived from classified news reporting, not from direct observation of institutions. A state is banded only where both violation and repair signal were seen; hatched states are unmeasured, not calm. Coverage is uneven, and repair is reported far less than violation, so shading tracks the press as well as the state.

State watchlist

Country Band Repair ρ Debt 30-day

Live event feed

Governance events classified by the rupture engine as violations or repairs, newest first. Click a row to inspect its country.

Methodology & sources

the model behind the map

Contradiction debt & rupture

Each state is scored from live governance events classified as violations (state breaches of its obligations) or repairs (credible steps to make good). Two decayed stocks accumulate per country — a violation stock V and a repair stock R_eff (90-day half-lives) — and drive:

  • Contradiction debt — the master instability quantity: D(t) = max(0, D(t‑1)·λ + cd_mult·Vₙₑw − repBonus·R_effₙₑw)
  • Repair ratio ρ — how well repair keeps pace with breach: ρ = (R_eff·repBonus + R_base) / max(V′, ε), where V′ is the violation stock after coverage and media-capture correction (see below).
  • Rupture bandstable ρ≥1.0 · strained 0.6≤ρ<1.0 · critical ρ<0.6 · imminent ρ<0.6 with debt rising.
  • No datano data the violation stock is below the minimum needed for ρ to mean anything. Absence of coverage is reported as such, never as stability.
  • Media-capture correction — events are gathered from each country's own press, which imports that press's freedom as a measurement bias in two directions at once: a captured press under-reports the state's violations and amplifies its reform announcements, and both errors push ρ up. V is divided by a visibility factor and R_eff multiplied by a repair-credibility factor, each interpolated from WGI Voice & Accountability and equal to 1.0 for a free press. Ingestion also unions foreign coverage for low-VA countries — a multiplier can rescale an observation but cannot create one the local press never made.

Every state launches at a stable baseline and can only escalate into a rupture band once real contradiction-debt history has accumulated (a short warm-up window) — so scores build credibly from the ground up rather than reacting to a single day of coverage.

Rule of law as a repair engine

A functioning legal order continuously repairs contradictions even when no single "repair event" makes the news. Following the Structural Ontology of Law (SOoL / SimLex) model, each country carries an absorption capacity A — the contradiction debt its legal order can hold before outstanding breaches stop being routine — and architecture coefficients (cd_mult, repBonus, Remedy-node weight) interpolated between a collapsed and a rule-of-law order by its Legal Order Capacity (LOC). LOC is built from World Bank Worldwide Governance Indicators — LOC = 0.6·RuleOfLaw + 0.25·ControlOfCorruption + 0.15·Voice&Accountability. All forms of legal repair count — judicial review, remedy, nullification of unlawful acts, and accountability — not only political concessions.

ρ is reported exactly as published: ρ = R_eff / V, with no institutional term added to it. Capacity acts on the threshold a state is judged against, not on its measured repair: escalation to critical or imminent requires contradiction debt above that state's absorption capacity A, interpolated from LOC. An earlier build instead added a standing repair constant into ρ's numerator, which made the reported ratio a different quantity from the published one and, at the values needed to keep consolidated democracies stable, held ρ permanently above the imminent threshold. Debt is also where the signal actually is: across the labelled set ρ alone barely separates the classes (median 0.17 for rupture cases vs 0.21 for stable controls), while debt separates them cleanly (median 3.67 vs 0.02).

Coverage-exposure normalization (currently off)

Status: this correction is implemented but disabled (α = 0) as of the 2026-08-02 recalibration. It was built when per-country coverage was wildly unequal, but the historical per-country sweep now collects each state on its own query, equalizing coverage by construction — so the volume differences that remain increasingly reflect real event frequency, and dividing by them corrects twice. Against the labelled set, re-enabling it at α = 0.5 loses 4 of 10 known ruptures. It stays in the codebase, and should be reconsidered if ingestion ever returns to uneven per-country coverage. The description below is how it behaves when enabled.

Raw violation volume tracks how heavily a country is covered and aggregated, not just how troubled it is: a large state folds a whole subcontinent of routine local incidents under one flag, so it can accrue a large violation stock from sheer incident count even when each incident is minor. To keep the score a measure of institutional stress rather than media footprint, the violation stock is coverage-normalized — V′ = V / E_i, with E_i = (violation_count / reference)^½ clamped to [1, 6] and the reference set at the 75th percentile of per-country counts. A country is therefore scored on violation intensity per unit of coverage. This distinguishes many-routine-incident states (e.g. India, average violation severity ≈ 0.56) from few-but-severe ones (e.g. Sudan, ≈ 0.83): the former normalize down out of the rupture band, while genuinely severe states — whose stock comes from intensity, not volume — stay flagged. E_i ≥ 1 by construction, so normalization only ever relaxes a high-coverage score and never pushes a quiet country toward rupture.

Data

Governance events are ingested from WorldMonitor plus curated open feeds (see below) and classified by a local LLM into the SOoL violation/repair taxonomy with per-event severity and confidence. Scores update every poll cycle; debt accumulates over time.

Sources & citation

Koepsell, David R. “Repair Capacity and Collapse: A Mechanistic Early-Warning Model of Political Rupture.” Stability: International Journal of Security & Development (2026). DOI 10.33534/sta.1042.

The engine operationalizes the Structural Ontology of the Law (SOoL) — its 8-node Minimum Legal Chain, 13-type contradiction typology, and Irreversible Accountability Test — and the SimLex / SimEthica simulation program.

Books by David R. Koepsell, J.D., Ph.D.

  • A Structural Ontology of the Law. Palgrave Macmillan (forthcoming, 2026).
  • The Geometry of the Good. EthicsPress, 2025.
  • Who Owns You? Science, Innovation and the Gene Patent Wars. Wiley-Blackwell, 2009.
  • The Ontology of Cyberspace. Open Court, 2000.