This study examines how decisions to report crime vary across population groups, testing the hypothesis that individuals possess “windows of surprise” – learned thresholds for institutional engagement – shaped by social, economic, and psychological factors. A cross-sectional online survey (n = 1948) presented participants with crime vignettes of increasing severity. K-means clustering identified three latent reporting profiles, with entropy values used to assess response variability. Cluster 1 (lower income, mixed employment) displayed the broadest reporting threshold and highest entropy, especially for low-severity offences. Cluster 0 (moderate income, stable employment) showed narrow, consistent thresholds. Cluster 2 (higher income, higher education) revealed context-sensitive patterns. Income, gender, education, religion, and household structure significantly differentiated clusters. Results indicate that crime reporting is shaped by structured cognitive filters rather than uniform offence recognition. While serious crimes prompt consistent reporting, lower-harm offences are unevenly interpreted, particularly in disadvantaged groups, raising concerns about representational equity in crime data and the need for policing strategies that acknowledge these disparities.
Gareth Stubbs (Thu,) studied this question.