How Categorization Shapes the Probability Weighting Function

The tendency to overweight low probability events and underweight high probability events stems from the categorical distinction between ``not happening,'' ``a chance,'' and ``happening.'' We demonstrate that there exist multiple intermediary categories within the probability space that produce additional inflection points. Across preregistered studies, sensitivity jumps when probabilities cross these boundaries. With numeric probabilities, left-digit changes amplify certainty equivalents (Study 1) and shift risky choices in incentive-aligned gambles (Study 2). With visual probabilities, pie-chart partitions at halves and quarters have the same effect (Study 3). Hierarchical CPT fits reveal systematically negative residuals at boundary-crossing pairs, and a reanalysis of Wu & Gonzalez (1996) exhibits the same signature (Study 4). Thus, probability weighting is not smooth between 0 and 1—it is punctuated by context-dependent inflection points that distort the space. Recognizing these format-specific categories clarifies when behavior shifts and offers actionable guidance for judgment and decision-making theory.