REAL-WORLD INTERPRETIVE
One-sentence brief
One dramatic run can be an accident of assumptions or randomness. Paired controls and ensembles show whether a claimed effect survives reasonable alternatives.
REAL-WORLD INTERPRETIVE
SIMULATION LITERACY
Ensembles, Counterfactuals, and Control Cases
Why responsible simulation compares branches, baselines, seeds, and model structures instead of publishing a single privileged run.
LEVEL 1
ORIENTATION
Why this matters
REAL-WORLD INTERPRETIVE
Three key points
- A control case establishes what happens without the tested change.
- Paired randomness isolates policy differences from population differences.
- Counterfactual branches must never be confused with the observed record.
LEVEL 2
WORKING BRIEF
Evidence, context, and limits
REAL-WORLD INTERPRETIVE
Baseline and control
A baseline is the comparison condition. It should be plausible, documented, and run with the same data and evaluation rules as the intervention case.
- Define the baseline before examining preferred results.
- Avoid a deliberately weak straw baseline.
- Preserve version identity.
REAL-WORLD INTERPRETIVE
Paired comparison
Using the same seed or matched synthetic cohort across policy variants reduces noise and makes differences more attributable to the policy contract.
- Pair inputs and randomness.
- Report both aggregate and worst-cohort differences.
- Do not reuse paired results as evidence about real people.
REAL-WORLD INTERPRETIVE
Ensemble
An ensemble combines multiple parameter sets, seeds, datasets, or model structures. The spread of outcomes can communicate uncertainty better than one central line.
- Explain whether members are independent.
- Show distribution, not only average.
- Do not let many near-duplicates simulate consensus.
REAL-WORLD INTERPRETIVE
Counterfactual branch
A counterfactual branch asks what would happen under a different event or policy. It is not observed history and may become less reliable as it moves farther from the branch point.
- Label divergence time and assumptions.
- Keep branch data separate.
- Do not use counterfactual harm as proof of actual intent.
REAL-WORLD INTERPRETIVE
Preserve failed runs
Failed baselines and adverse scenarios are important evidence. Removing them after a correction prevents regression testing and creates an unrealistically clean history.
- Record failure criteria.
- Explain the correction.
- Retest the prior failure after changes.
REAL-WORLD INTERPRETIVE
Interpretation discipline
Agreement across runs strengthens a conclusion only when the ensemble spans credible uncertainty. Disagreement is informative and should guide collection, review, or narrower claims.
- Investigate structural disagreement.
- Use uncertainty to prioritize evidence.
- Avoid majority-vote truth.
LEVEL 3
COMPLETE DOSSIER
Limitations, game links, and review context
DISPUTED / MULTIPLE ACCOUNTS
Known limitations and gaps
- This is a non-operational educational transformation: it does not build or implement a game, executable simulator, forecasting service, emergency tool, or decision system.
- This page is an educational transformation of supplied research leads; it does not authenticate every citation, equation, product claim, or institutional attribution in those files.
- A scenario, model run, or map is not an observation, forecast, legal finding, public-health instruction, emergency warning, or proof of future behavior.
- No source code, nuclear-effects formula, casualty calculation, target-selection method, cyber-intrusion procedure, exploit chain, or instruction for bypassing safeguards is published.
- Geography, nationality, ethnicity, religion, language, migration, disability, health, poverty, or political identity are not inherent danger, compliance, intelligence, competence, or worth variables.
- Specialist scientific, public-health, accessibility, legal, regional, ethics, security, and lived-experience review remains pending; the page stays open to correction.
GAME MECHANIC
RogueIntelligence.org connections
- Evidence and uncertainty methodUse provenance, confidence, alternatives, and correction before interpreting a model.
- Synthetic-cohort fairness gatesSee a bounded repository example where a failed baseline remains visible and human approval stays separate.
- International comparison methodApply equal analytical method without making one country or data environment the default.
REAL-WORLD INTERPRETIVE
Glossary cross-reference
Terms are defined for this site’s evidence method, not as universal legal or clinical definitions.
LEVEL 4
RESEARCH EDITION
Sources, methods, and stable links
REAL-WORLD INTERPRETIVE
Linked reports
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Building Epidemiological ModelsProtected research reference; no public report route in this release.
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IARPA SimEarth Game Architecture part 2Protected research reference; no public report route in this release.
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Planetary Simulation Game ArchitectureProtected research reference; no public report route in this release.
REAL-WORLD VERIFIED
Method and corrections
This page follows the public method for provenance, confidence, source independence, alternative accounts, limitations, review state, and visible correction.
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