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Offending risk factors and area: an investigation using structural equation modelling

Cunliffe, Jack (2015) Offending risk factors and area: an investigation using structural equation modelling. PhD thesis, London School of Economics and Political Science.

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This thesis has two main aims. The first is substantive: to investigate whether and how an individual’s perceptions of their area act as risk factors for offending. The second is methodological: to demonstrate that theoretically-informed structural equation modelling can make best use of existing and often under-utilised datasets, particularly cross-national studies such as those typically conducted by large-scale organisations or governments. Using the United Kingdom Offending, Crime and Justice Survey (OCJS) conducted between 2003 and 2006, and taking a range of questions on individual perceptions, family circumstance, self-reported offending and variables relating to the area in which the respondent lives, the work reviews previous criminological measurement constructs of well-known risk factors (from both an analytical and theoretical perspective) and once these are defined moves on to examine self-report offending using structural equation modelling. Findings are predominantly consistent with previous work and show that individual criminogenic propensities matter most, but also that a complex interrelationship of area perceptions operate in conflicting directions. Once this is accounted for, living in an area with higher disorder seems to increase self-report offending, with part of the relationship explained by perceptions of lower collective efficacy. However, this relationship seems to operate only at one time point and when looking longitudinally it appears that it is the family situation that takes precedence. This leads in turn to mixed policy implications. In the short-term, it appears that interventions to address perception of area would be most successful to combat offending behaviour but over the longer term addressing the family situation would be more appropriate. Implications for data collection processes and analytical approaches to existing data are centred on the simple analytical framework that pays equal attention to the set of questions: 1) What can be measured? 2) Can these measures be structured? 3) What are the results?

Item Type: Thesis (PhD)
Additional Information: © 2015 Jack Cunliffe
Library of Congress subject classification: H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Sets: Departments > Social Policy
Supervisor: Hills, John

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