After 30+ journal entries, calculate your calibration…

When This Fires

• After accumulating 30+ decision journal entries (Decision journal entries need six fields captured before…) with confidence percentages
• During quarterly calibration reviews when you have enough data to group meaningfully
• When you suspect you're systematically overconfident or underconfident
• When building a personal calibration curve that improves over years of decision-tracking

Common Failure Mode

Skipping the confidence percentage during journaling (Decision journal entries need six fields captured before…) because "I don't know what number to put." Any number is better than none. The accuracy of the initial number doesn't matter — what matters is that the number exists so it can be calibrated over time. Your first 30 entries will have poorly calibrated percentages; your next 30 will be better because you've seen your calibration curve.

The Protocol

(1) After 30+ journal entries, group entries by stated confidence level. Typical buckets: 50-59%, 60-69%, 70-79%, 80-89%, 90-100%. (2) For each bucket, calculate: what percentage of predictions in this bucket actually came true? (3) Compare each bucket's actual rate to its stated confidence. Perfect calibration: 70% bucket → 70% actual. (4) Identify your calibration pattern: overconfident (actual < stated) is most common. Underconfident (actual > stated) is rarer but possible. (5) Apply the correction: if your 80% predictions come true 65% of the time, your personal "80% confident" maps to ~65% real probability. Adjust future decisions accordingly — build more contingency, gather more information, or reduce commitment size for the actual confidence level. (6) Re-calculate every 30 entries. Calibration improves with practice — watching your calibration curve tighten over time is itself motivating.