Purpose
Organised Crime is notoriously difficult to define and measure, resulting in limited empirical evidence to inform policy makers and practitioners. This study explores the feasibility of identifying a greater number of organized crime offenders, currently captured (but invisible), within an existing national general crime database.
Methodology
All 2.1 million recorded offenders, captured over a four year period on the UK Police National Computer (PNC), were filtered across three criteria associated with organized crime (co-offending, commission of specific offences, three years imprisonment or more). The 4109 ‘organized crime’ offenders, identified by the process, were compared with ‘general’ and ‘serious’ offender control groups across a variety of personal and demographic variables.
Findings
Organized crime prosecutions are not random but concentrate in specific geographic areas and constitute 0.2% of the offender population. Offenders can be differentiated from general crime offenders on such measures as: criminal onset age, offence type and criminal recidivism.
Research implications
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 organized crime, generating richer evidence on which policy makers and practitioners can more effectively deliver preventative and disruptive tactics.
Originality
This is the first time an ‘offence based’ methodology has been used in differentiating organised crime from other offenders in a general crime database
