Organised Crime is notoriously difficult to identify and measure, resulting in limited empirical evidence to inform policy makers and practitioners. The purpose of this paper is to explore the feasibility of identifying a greater number of organised crime offenders, currently captured but invisible, within existing national general crime databases.
All 2.1 million recorded offenders, captured over a four-year period on the UK Police National Computer, were filtered across three criteria associated with organised crime (co-offending, commission of specific offences, three years imprisonment or more). The 4,109 “organized crime” offenders, identified by the process, were compared with “general” and “serious” offender control groups across a variety of personal and demographic variables.
Organised crime prosecutions are not random but concentrate in specific geographic areas and constitute 0.2 per cent of the offender population. Offenders can be differentiated from general crime offenders on such measures as: diversity of nationality and ethnicity, onset age, offence type and criminal recidivism.
Using an offence-based methodology, rather than relying on offenders identified through police proactive investigations, can provide empirical information from existing data sets, across a diverse range of legislative areas and cultures. This allows academics to enhance their analysis of organised crime, generating richer evidence on which policy makers and practitioners can more effectively deliver preventative and disruptive tactics.
This is the first time an “offence based” methodology has been used to differentiate organised crime offenders from other offenders in a general crime database.
The authors thank to Michael Skidmore who provided support and logistics.
This paper is in memory of the authors’ dear friend and colleague Professor Keith Soothill, who was involved with this project, and who sadly passed away in February 2014.
Kirby, S., Francis, B., Humphreys, L. and Soothill, K. (2016), "Using the UK general offender database as a means to measure and analyse organized crime", Policing: An International Journal, Vol. 39 No. 1, pp. 78-94. https://doi.org/10.1108/PIJPSM-03-2015-0024
Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited