Research Project

An evaluation of a pilot project on 'Intelligence-orientated Neighbourhood Security Interviews' (i-NSI)

Researchers: Alexis Cran (Strathclyde Police), Niall Hamilton-Smith (University of Stirling) & Simon Mackenzie (University of Glasgow)

Summary: Aims & Objectives:

The aim of this report is to evaluate the recent community intelligence project (i-NSI) carried out in the Inverclyde area of K Division, Strathclyde Police. The project involved the implementation of 'intelligence-orientated Neighbourhood Security Interviews' (known as i-NSI). Originally developed by Martin Innes and colleagues Surrey University, i-NSI is an IT-supported method for police personnel to conduct interviews with community members.

The evaluation has a number of key objectives. These are:


The i-NSI process was developed as part of the National Reassurance Policing Programme and is designed to guide the systematic collection of community intelligence in a way that facilitates and informs policing responses that are consistent with the principles of the Signal Crimes Perspective.

The Signal Crimes Perspective, as principally developed by Innes (2004), critiques earlier criminological models that present a linear relationship between local disorder, fear of crime and actual crime levels (e.g. principally the 'broken windows' thesis of Wilson and Kelling, 1982). Innes, demonstrated that measured 'fear of crime' often fails to correspond to a particular level of crime, nevertheless he highlighted the importance of often 'trivial' local incivilities in informing people's judgements about risk.

Innes developed an approach for unpacking how people interpret crime and disorder, focussing on how a particular crime or disorder incident is 'expressed' (how somebody describes the crime or disorder), its effect (how it impacts on them in terms of behaviour, thinking, or feelings), and finally its content (how the incident informs their sense of risk or threat) (Innes 2007). These elements together constitute a 'signal', and for Innes it is identifying, analysing and targeting the most prominent signals within a community that is key to successful reassurance policing. What is required to combat 'signal crimes' and 'signal disorders' are effectively tailored 'control signals' (typically deriving from police actions) that if tailored well may have a positive impact on peoples' sense of security (Innes 2004). So the advantage of SCP, is that rather than focussing on crimes or disorders that may be prominent in police statistics but which may not be prominent in informing a particular communities' sense of order and control - or conversely focussing on vague measures of 'fear of crime', signal crimes and disorders are inherently grounded and 'citizen focussed' (Innes 2005, p. 195), targeting police resources on incidents that are most visible and impactful in a specific community.

Consequently, SCP provides a framework for generating a particular sort of community intelligence that in turn allows the police to target their efforts on those issues that are having a disproportionate impact on a given community. To facilitate and ensure the robust implementation of SCP, Innes and colleagues developed software and a database especially designed for the purpose of collecting, mapping and analysing signal crimes and disorder (i-NSI). This IT-driven solution has now been used in several UK police forces (including South Wales Police and Lancashire Constabulary), by local authorities (notably the London Borough of Sutton) and internationally (by the police in the Netherlands and Victoria Police in Australia). Results from these areas where this community intelligence approach has already been used are reportedly encouraging.

The Strathclyde i-NSI pilot:

The pilot was run in 2011 with the principal aims of testing whether this approach improved the capture of community information on those local crimes and disorders that emitted the strongest 'signal' in terms of being key drivers of community anxiety, and to assess in turn whether this information could be usefully collated and analysed to inform policing responses that might, in turn, better reassure and boost community confidence in the police.

The intelligence from neighbourhood security interviews identifies the signals impacting on community confidence. The results provide a mechanism to help improve the response of Police and partners to community concerns and needs.

For the results of the evaluation and recommendations, please see the Full Report

Publications: Full Report [November 2012]


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