Criminometrics treats crime as an econometric object. This paper argues that such ambition cannot scale under current institutions. Crime categories are socially and legally contingent, and crime data are administrative artifacts shaped by reporting, recording, and enforcement. The result is unstable measurement and reflexive feedback that blurs predictive accuracy and fairness with policing practices. Using examples of hotspot prediction, local forecasting, and risk-scoring techniques, and reviewing statistical and causal approaches to bias and tangled cause-and-effect, the paper shows that accuracy gains are setting-specific and often optimize administration more than understanding. It concludes by urging methodological pluralism and ethical scrutiny.
Henry Prunckun (Mon,) studied this question.