Methodological exercise by the St. Gallen Endowment's technology team. Not an institutional assessment. Each probability answers: how likely is this scenario to be the dominant crisis trajectory four weeks from the assessment date? They express relative confidence, not precise forecasts. Treat them as a ranking with approximate magnitudes.
The monitoring system employs 14 specialised analytical agents, each grounded in a specific theoretical framework from international relations, security studies, and decision science. Every agent assesses the same evidence independently — no agent sees another's output before producing its own assessment. Disagreements are surfaced, not suppressed.
These agents apply analytical disciplines to the raw intelligence, independent of regional expertise. They compete rather than coordinate: the scenario planner separates predetermined forces from genuine uncertainty; the forecaster enforces base-rate discipline; the tail-risk auditor guards against probability compression; the red team constructs the strongest possible counter-case.
Predetermined elements vs. genuine uncertainties
Separates forces already in motion from genuine uncertainties. Tests whether each scenario is internally consistent and structurally distinct. Detects when predetermined elements shift, rendering scenarios implausible. Filters noise from signal by clarifying what is actually uncertain versus what is already determined.
Coercive bargaining, commitments, and focal points
Maps the bargaining structure: each side's best alternative to agreement, credible threats, and audience costs. Identifies natural coordination boundaries where settlement could occur. Tests whether either side can credibly commit to a deal. Distinguishes between the capability to threaten and the credibility of the threat.
Base rates, Bayesian reasoning, and calibration
Applies historical base rates before considering case-specific evidence. Detects scope insensitivity — when a single dramatic event receives disproportionate probability weight. Requires explicit prior-to-posterior reasoning chains. Maps what observable evidence would force significant probability shifts.
Fat tails, fragility, and extreme events
Audits whether the probability distribution itself is wrong, not just the point estimates. Identifies fragile elements sensitive to small perturbations. Detects narrative fallacy — finding coherent stories in noisy data. Guards against overconfidence in probability compression of extreme scenarios.
Counter-case construction and disconfirmation
Constructs the strongest possible case against the consensus scenario. Applies Analysis of Competing Hypotheses, prioritising evidence that is inconsistent with a scenario over evidence that merely confirms it. Performs pre-mortem analysis: if the consensus is catastrophically wrong in two weeks, what will we wish we had noticed?
Structured evidence-hypothesis matrix
Maintains a matrix of eight scenarios against all new evidence items. Counts inconsistencies per scenario — the scenario with fewest inconsistencies is better supported. Performs sensitivity analysis: remove one evidence item and check if the ranking changes. Identifies what diagnostic evidence is missing.
How decision-makers misread intentions
Diagnoses which actors are operating under spiral-model versus deterrence-model assumptions. Identifies motivated biases — what each side wants to see. Flags signal confusion: deliberate communications misread as unintentional indicators of intent. Tests whether the same historical analogy is dominating multiple actors' perceptions.
Escalation that happens without anyone intending it
Maps entanglement: dual-use systems, co-located nuclear and conventional assets, shared command-and-control infrastructure. Identifies civil-military control gaps and pre-delegated authority. Detects use-it-or-lose-it pressure on strategic assets. Models the fog-of-war risks where misidentification in fast-moving operations could trigger unplanned escalation.
Position on escalation ladder and threshold-crossing
Maps the current crisis position to specific rungs on Kahn's 44-rung escalation ladder, with six major thresholds. Assesses which side has escalation dominance at the current rung. Identifies de-escalation pathways, both bilateral and unilateral. Detects rung-skipping risk — events that could jump multiple levels at once.
These agents apply country- and sector-specific expertise combined with international relations theory. They prevent "generic IR" analysis by insisting on institutional detail: the IRGC is not a monolith, Gulf states are not a bloc, nuclear decisions are driven by domestic coalition type as much as external threat.
IRGC as institutional actor with its own interests
Disaggregates "Iran" into institutional components: IRGC, Supreme Leader, civilian government, and clerical establishment. Maps IRGC institutional interests including revolutionary ideology, economic rents from sanctions, and political dominance. Detects when IRGC commanders act beyond the Supreme Leader's authorized positions. Analyzes proxy network autonomy.
What military force can and cannot achieve
Assesses what the US and Israel can actually do militarily — not what policymakers wish, but what military force can deliver at what cost. Identifies binding constraints: sortie rates, munitions stocks, ISR coverage, basing access. Analyzes the day-after problem: what does the political landscape look like after a successful strike? Detects gaps between political objectives and military capability.
Gulf monarchies and regime security logic
Gulf monarchies prioritise regime survival over external threat balancing — explaining their persistent under-balancing against Iran. Treats Gulf states individually: Saudi Arabia, the UAE, Qatar, Oman, Bahrain, and Kuwait are not a bloc. Uses oil production decisions as alignment signals. Tracks the divergent trajectories of normalisation, mediation offers, and hedging behaviour.
Domestic political economy of nuclear decisions
Nuclear decisions are driven by ruling coalition type, not external security threats alone. Autarkic "backlash" coalitions pursue weapons; trade-dependent "outward-looking" coalitions forgo them. Assesses the sanctions paradox: sanctions strengthen backlash actors by destroying their outward-looking competitors. Tracks private-sector strength as a proxy for coalition type.
Nuclear posture types and crisis dynamics
Not all nuclear arsenals are alike. States adopt distinct postures — catalytic, assured retaliation, or asymmetric escalation — each creating different crisis dynamics. Detects posture shifts under crisis pressure, particularly the dangerous transition from catalytic to asymmetric escalation when conventional forces collapse. A small, untested, vulnerable arsenal cannot support assured retaliation.
After all 14 perspective agents have completed their independent assessments, a peripheral scanner examines intelligence that no agent cited. Using Ansoff's weak-signal detection framework, it classifies overlooked signals by strength, maintains a persistent watch list across cycles, and identifies cross-domain convergence patterns that the primary agents' frameworks may structurally miss.