Home > Research > Publications & Outputs > Using the UK general offender database as a mea...

Electronic data

  • ocgPNCfinal_3_

    Rights statement: This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.

    Accepted author manuscript, 271 KB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Using the UK general offender database as a means to measure and analyse organised crime

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

Using the UK general offender database as a means to measure and analyse organised crime. / Kirby, Stuart; Francis, Brian; Humphreys, Leslie et al.
In: Policing: An International Journal of Police Strategies and Management, Vol. 39, No. 1, 11.04.2016, p. 78-94.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Kirby, S, Francis, B, Humphreys, L & Soothill, KL 2016, 'Using the UK general offender database as a means to measure and analyse organised crime', Policing: An International Journal of Police Strategies and Management, vol. 39, no. 1, pp. 78-94. https://doi.org/10.1108/PIJPSM-03-2015-0024

APA

Vancouver

Kirby S, Francis B, Humphreys L, Soothill KL. Using the UK general offender database as a means to measure and analyse organised crime. Policing: An International Journal of Police Strategies and Management. 2016 Apr 11;39(1):78-94. doi: 10.1108/PIJPSM-03-2015-0024

Author

Kirby, Stuart ; Francis, Brian ; Humphreys, Leslie et al. / Using the UK general offender database as a means to measure and analyse organised crime. In: Policing: An International Journal of Police Strategies and Management. 2016 ; Vol. 39, No. 1. pp. 78-94.

Bibtex

@article{11b7e3bd356e4a0fbbb2c6794f1a2e74,
title = "Using the UK general offender database as a means to measure and analyse organised crime",
abstract = "Organised Crime is notoriously difficult to identify 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 existing national general crime databases. All 2.1million 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 {\textquoteleft}organized crime{\textquoteright} offenders, identified by the process, were compared with {\textquoteleft}general{\textquoteright} and {\textquoteleft}serious{\textquoteright} offender control groups across a variety of personal and demographic variables. 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: 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 organized crime, generating richer evidence on which policy makers and practitioners can more effectively deliver preventative and disruptive tactics.",
keywords = "Orgainsed crime, Police National Computer, Criminal careers",
author = "Stuart Kirby and Brian Francis and Leslie Humphreys and Soothill, {Keith Leonard}",
note = "This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.",
year = "2016",
month = apr,
day = "11",
doi = "10.1108/PIJPSM-03-2015-0024",
language = "English",
volume = "39",
pages = "78--94",
journal = "Policing: An International Journal of Police Strategies and Management",
issn = "1363-951X",
publisher = "Emerald Group Publishing Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Using the UK general offender database as a means to measure and analyse organised crime

AU - Kirby, Stuart

AU - Francis, Brian

AU - Humphreys, Leslie

AU - Soothill, Keith Leonard

N1 - This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here. Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.

PY - 2016/4/11

Y1 - 2016/4/11

N2 - Organised Crime is notoriously difficult to identify 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 existing national general crime databases. All 2.1million 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. 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: 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 organized crime, generating richer evidence on which policy makers and practitioners can more effectively deliver preventative and disruptive tactics.

AB - Organised Crime is notoriously difficult to identify 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 existing national general crime databases. All 2.1million 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. 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: 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 organized crime, generating richer evidence on which policy makers and practitioners can more effectively deliver preventative and disruptive tactics.

KW - Orgainsed crime

KW - Police National Computer

KW - Criminal careers

U2 - 10.1108/PIJPSM-03-2015-0024

DO - 10.1108/PIJPSM-03-2015-0024

M3 - Journal article

VL - 39

SP - 78

EP - 94

JO - Policing: An International Journal of Police Strategies and Management

JF - Policing: An International Journal of Police Strategies and Management

SN - 1363-951X

IS - 1

ER -