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futures-calibration

Research
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Aggregate probability judgments across perspectives using Real-Time Delphi or prediction market mechanisms.

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Futures Calibration

Purpose: Aggregate probabilistic forecasts from multiple perspectives into calibrated predictions. Uses Real-Time Delphi continuous updating or prediction market scoring to produce well-calibrated probability estimates for future events.

When to use:

  • Technology timeline estimation
  • Market forecasts requiring multiple expert inputs
  • Risk probability assessment
  • Any question framed as "what is the probability that X by time T?"

Budget

ParameterConstraint
Rounds2–3 (continuous updating preferred)
Perspectives≥4 independent forecasters
Calibration targetBrier score improvement across rounds

State Ledger

KeyTypeDescription
questionstringThe forecasting question
time_horizonstringWhen the event would resolve
perspectivesarrayList of forecaster perspectives
roundsarrayHistory of probability estimates
current_aggregatefloatCurrent aggregated probability
calibration_metricsobjectBrier score, log score tracking

Available Tactics

  • iterative-convergence-round — Adapted for probability estimates
  • threshold-calibration — Determine confidence bands

Available SOPs

  • judgment-collection
  • feedback-distribution
  • consensus-measurement
  • round-decision
  • threshold-sweep
  • consensus-synthesis

Execution Guidance

  1. Frame question with clear resolution criteria and time horizon
  2. Collect initial probability estimates with reasoning
  3. Share aggregate and reasoning (anonymized) each round
  4. Track whether estimates are converging or polarizing
  5. Report final calibrated estimate with confidence interval

Output Format

forecast_question: <question>
time_horizon: <date/period>
calibrated_probability: <float 0-1>
confidence_interval: [lower, upper]
rounds_completed: <int>
convergence_pattern: converging/stable/polarizing
key_considerations: [...]

Available Tactics

Optional, no fixed order; the final leaf is always a sop.

TacticWhen to use
iterative-convergence-roundExecute one full Delphi round — collect judgments, distribute anonymous feedback, measure consensus, decide whether to continue.
threshold-calibrationSystematically sweep consensus thresholds to observe which items achieve consensus at what level, producing a threshold-consensus curve.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
consensus-synthesisSynthesize all rounds into a final consensus report documenting agreements, dissent, and process.