What a model card is forThis page exists so any Warconomy forecast produced by this model can be audited: what it assumes, where it breaks, how its uncertainty is built, and what simple baseline it must beat to be worth running. Forecasts are decision-support, not advice.
At a glance
| Model ID | policy-sequencing-v1 |
|---|---|
| Version | 1.0 |
| Method family | expert defined scenario |
| Intended use | Estimate the likelihood that a named institution takes a defined, publicly-observable policy action within a stated window, based on its own announced process, precedent timing, and required approval thresholds. |
| Update cadence | per event |
| Analyst judgment | Yes — a human sets or adjusts key parameters (see below) |
| Forecasts using it | 1 |
Assumptions
- The institution follows its stated procedural sequence (proposal, negotiation, adoption) rather than acting outside it.
- Historical timing between an equivalent proposal and adoption is informative about the current one.
- Publicly-stated intent by decision-makers is meaningful evidence, though not binding.
Known weaknesses and failure conditions
- Unanimity- or consensus-based bodies can be blocked indefinitely by a single holdout, which precedent timing systematically under-weights.
- Announced target dates routinely slip without any public correction.
- Relies on reported negotiating positions that are often second-hand and contested.
How uncertainty is built
Expressed as a coarse probability band only (very-unlikely through very-likely), never a decimal percentage, because the reference class of comparable past decisions is small.
Validation and baseline comparison
Scored on resolution against the institution's own published legal act (its official journal or press release), and compared against a base-rate baseline derived from how often comparable proposals were adopted within a similar window.
Model change history
| Version | Change |
|---|---|
| 1.0 | Initial production release of this model card, issued with Warconomy's first forecast portfolio. |
Model versions are immutable. A material methodology change produces a new version, and forecasts issued under the old version keep pointing at the version that produced them.
Forecasts produced by this model
Related
All forecasting methods · Responsible forecasting policy · Active forecasts · Track record