Young offenders, schools and the neighbourhood

A new approach to data‐analysis for community policing

Bibliographic Data

ID12396604
AuthorsTom Williamson (0000-0002-9726-0209, University of Portsmouth, corresponding author), David Ashby (0000-0002-6858-5485, University College London), David I Ashby, Richard Webber (0000-0001-6584-0527, University College London)
Year2005
Volume15
Issue3
Pages203-228
Publication date2005-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Community & Applied Social Psychology (JOURNAL)
Journal identifiersISSN: 1052-9284 • E-ISSN: 1099-1298
PublisherWiley (PUBLISHER • GB)
DOI10.1002/casp.817
OpenAlexW2073533659
LanguageEN
Citations received8
References cited16

Youth offending often lies at the heart of community policing programmes. The primary objective of this study is to provide evidence of the extent to which the level and the pattern of youth offending varies between different types of neighbourhood and the schools they attend. We posit that the adoption of neighbourhood typology based analyses, frequently used in the commercial world, are appropriate to address this issue. We substantiate this argument with the analysis of a large anonymized database ( c . 34,000 records spanning 5 years) containing the details of youth offenders and their offences in Nottinghamshire, segmented by neighbourhood type. The neighbourhood classification used, a proprietary geodemographic solution, is based on both census and consumer data, and segments all UK postcodes into 61 neighbourhood types and 11 aggregate groups. The results are analysed with reference to nine conditions: level of offending (total numbers of offences and offenders); single/repeat offenders; gender; ethnicity; offence classification; outcome; context (including temporal conditions such as school holidays); whether the offender accepted or denied occurrence; and age at the time of the occurrence. Of particular interest is the association between the offenders and educational establishments, and thus the identification of schools that are most at risk for recidivism, raising questions regarding the concept of criminogenic schools. A number of policy recommendations are made which could lead to better informed strategy management in youth offending. We conclude that geodemographic analysis can leverage extra value and substantial insight from operational data bases collected on a routine basis. However, this poses the question as to why public sector practitioners and planners have not already made use of such analytical techniques, which have been central to much business strategy in recent years. This approach to the analysis of youth offender data lends itself to further social psychological research and exploration. Copyright © 2005 John Wiley & Sons, Ltd

Criminology · Neighbourhood (mathematics · Sociology · Typology · Crime Patterns and Interventions · Crime, Illicit Activities, and Governance · Psychology · Wildlife Conservation and Criminology Analyses

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