Policing Records As Epistemic Error: When “Crime Data” Is Institutional Output
- IJLLR Journal
- Jan 29
- 1 min read
Ishaan D. Joshi, Consulting Forensic and Criminal Intelligence Expert, Visiting Faculty, MIT-WPU School of Law
ABSTRACT
Police-recorded crime statistics are routinely treated as neutral indicators of “crime levels” and used to justify downstream governance choices—from hotspot patrols to predictive policing. This article argues that such records are better understood as institutional outputs: products of discretionary classification, incentive structures, organisational routines, and unequal visibility generated by policing itself. The epistemic difference between crime-as-lived harm, crime-as-reported, and crime-as-recorded enforcement is therefore not a technical footnote but a rule-of-law problem when police records become proxies for social harm in coercive decision-making. Drawing on criminology, public administration, and surveillance studies, the article identifies three systematic distortion mechanisms: (i) differential reporting and social silence; (ii) street-level discretion and performance regimes shaping recording practices; and (iii) surveillance intensity producing self-confirming enforcement maps that are easily mistaken for harm maps. It then develops a legal-analytic framework for the state’s use of such proxies in coercive domains: proxy humility, anti-circularity duties to prevent feedback loops, and rights-weighted error governance that treats false positives as constitutionally costly. Finally, it proposes a minimum epistemic duty of candour: a public-law obligation to disclose known proxy limitations, circularity risks, and contestability pathways whenever police records materially influence exposure to policing. The article concludes that legitimacy in data-driven policing depends less on improved prediction and more on constitutionalising the epistemic conditions under which institutional data can claim authority.
Keywords: police-recorded crime; epistemic error; street-level bureaucracy; surveillance intensity; predictive policing
