Chainey, S; Sidebottom, A; Bowers, K; Wortley, R; Baudains, P; (2015) Project MARGIN: Conceptual report: defining the indicators defining demographic, socioeconomic and socio-geographic determinants of insecurity. UCL Jill Dando Institute of Security and Crime Science and Project MARGIN: London, UK.

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Abstract

In Deliverable 2.1 of the MARGIN project, a database was collated to enable a comparative analysis between police recorded crime data and crime victimisation surveys across five European countries. In the present report, we present such an analysis in order to identify a range of demographic, socioeconomic, and socio-geographic determinants of insecurity. The available data enable two dimensions of insecurity to be addressed. The first, victimisation, can be measured through two sources: police recorded crime data and responses to questions regarding victimisation in a crime victimisation survey. This dimension of insecurity is known in the MARGIN project as the objective dimension as it attempts to capture individuals’ actual experiences with crime. The second, perceived insecurity, relates to questions in the crime victimisation survey surrounding respondents’ thoughts about crime, safety, and how their perceptions about crime alter their habits. This aspect is known as the subjective dimension. It has been shown previously that, although related, perceived insecurity and victimisation capture different aspects of insecurity. Moreover, there are some instances where people who have a very small risk of experiencing victimisation in fact have very high levels of perceived insecurity (see Doran and Burgess (2012) for a review). In this report, we analyse consistencies in the MARGIN database with respect to a range of indicators of insecurity. It is important to determine indicators of insecurity in order to identify marginalised communities who tend to experience a disproportionate amount of victimisation and who also have high levels of perceived insecurity and fear of crime. Identification of such communities can enable directed policies to reduce levels of insecurity. The results of this analysis are intended to inform the development of the MARGIN victimisation survey being developed in Work Package 4. In what follows, we first conceptualise the objective dimension by examining victimisation rates across the different study areas, as obtained from both police recorded crime and victimisation survey data. Next, we consider the subjective dimension by considering questions relating to different aspects of perceived insecurity. After describing a number of problems that arise when attempting to directly compare questions across the different victimisation surveys, we turn to the identification of a range of demographic and socioeconomic indicators which we find to be associated with particular aspects of perceived insecurity. We present the results of a range of regression analyses performed with this data. Finally, we discuss a range of potential sociogeographic indicators of insecurity, focusing particularly on the example of street robbery in Barcelona. We also discuss a range of other points to be considered in the identification of marginalised communities.

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