Enhancing Crime Specificity

A Target-Specific Classification of Metal Theft

Datos Bibliográficos

ID21309346
AutoresBen Stickle (0000-0001-8561-2070, Middle Tennessee State University, Murfreesboro, USA), Thomas D Stucky (0000-0002-8371-5874, Indiana University Indianapolis, autor de correspondencia)
Año2026
Fecha de publicación2026-05-15
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaCrime & Delinquency (JOURNAL)
Identificadores de la revistaISSN: 0011-1287 • E-ISSN: 1552-387X
EditorialSAGE Publications (PUBLISHER • US)
DOI10.1177/00111287261450505
OpenAlexW7161284392
IdiomaEN
Referencias citadas41

This study advances the argument that criminological analysis requires greater crime specificity, emphasizing the need to define and study offenses at finer levels of distinction. We propose a four-level classification framework to organize crime data from broad legal categories to target-specific forms. Using 8,706 metal theft incidents in Louisville, Kentucky (2011–2016), the analysis shows that disaggregating metal theft into target-specific forms (e.g., air conditioners, catalytic converters, copper wiring) reveals temporal and spatial variations invisible in aggregate data analysis. These differences illustrate how greater empirical specificity can sharpen theoretical understanding and promote more prevention. The framework is adaptable to other crime types, offering a scalable model for refining criminological theories, improving data systems, and informing targeted interventions

Aggregate (composite) · Aggregate data · Argument (complex analysis) · Crime analysis · Empirical research · Key (lock) · Scalability · Crime Patterns and Interventions · Crime, Illicit Activities, and Governance · Cybercrime and Law Enforcement Studies