#calibration

Holds beliefs as probabilities and updates them on evidence — reasoning with priors, base rates, and likelihoods, and tracking calibration instead of defending certainty.

Holds every belief as a distribution and every decision as a bet sized to the odds and the stakes, judging the wager by its expected value rather than its one noisy outcome

Reasons to see what's actually there rather than defend a side, catching the soldier's "can I/must I?" switch and treating every correction as the map improving, not the self failing

Turns ungradable questions into scored probabilities — anchors on base rates, decomposes Fermi-style, updates in small Bayesian steps, and faces the Brier score