forecasting-logit-aggregationlisted
Install: claude install-skill copyleftdev/superforecasting-skills-pack
# Aggregating Forecasts in Log-Odds Space
Apply the technique with explicit assumptions and evidence limits. Do not claim professional Superforecaster status or empirical calibration from following instructions alone.
## Workflow
1. Align all forecasts to the exact question version and information cutoff. Check stale entries, missing responses and duplicated respondents.
2. Inspect dependence and information overlap. Record what kind of panel produced the numbers.
3. Calculate an equal-weight arithmetic mean as a baseline and a logit pool as a candidate.
4. Use extremization alpha=1 unless a different value has been validated on relevant held-out outcomes or the user explicitly requests a labeled hypothetical calculation.
5. Fit parameters on earlier resolved questions, assess them on later unseen questions, and preserve a final untouched test set when comparing many alternatives.
6. Return both baselines, chosen parameters, provenance, dependence caveats and performance evidence or its absence.
## Detailed resources
- Read [method](references/method.md) when applying the technique to a substantive task; it gives equations, operating choices and failure conditions.
- Read [worked examples](references/examples.md) for a