Chainey, S; Macdonald, I; (2012) Stop and search, the use of intelligence and geographic targeting: Findings from case study research. National Policing Improvement Agency: London, UK.

Text 121122_Stop_and_search_targeting_Full_report_PQ.pdf Access restricted to UCL open access staff Download (2MB)

Abstract

This report presents findings from research carried out in the mid-2000s to examine the role played by intelligence in police stop and search practices. Earlier research evidence has suggested the effective use of intelligence in stop and search can help maximize both the effectiveness and the fairness of the power. The report addresses three questions: 1. To what extent was intelligence used by police in their routine use of stop and search? 2. To what extent were statistical and geographical patterns of searches consistent with the application of intelligence to search practices? 3. What are the potential implications of the application of intelligence for race disproportionality in stop and search? To address these questions, the study relied on in-depth interviews with operational officers from two police force areas, and statistical and geographical analysis of search records from five case study sites. Stop and search decision-making and intelligence Interviews with police officers and intelligence officers/analysts showed that the following: - Intelligence was highly valued by police officers. They learned about it in regular shift briefings, and some also self-briefed using force intelligence system. - Intelligence was reported to be important in guiding their stop and search activities. In particular, hotspot analyses helped guide police officers geographically, and information on active offenders was also said to direct their attention to certain individuals. However, there was some evidence to suggest officers tended to focus more on the intelligence that was in line with their prior knowledge. - A number of obstacles were identified during the research to the effective application of intelligence to stop and search: o The need to respond to calls for service meant that officers often felt they had limited time to carry out proactive intelligence-led stop and search. o Officers often felt judged by supervisors on the quantity of searches they carried out. At times, this may have distracted them from an intelligence-based approach. o Because officers had a relatively broad understanding of what constituted intelligence, there was a view that they may often act on low grade information without regard to its quality. o Officers sometimes faced difficulties recalling the detailed intelligence provided in briefings because of an overload of intelligence information. Stop and search patterns and intelligence - Statistical and geographical analysis showed that the patterns of recorded searches in the five case study forces were not always consistent with what might have been expected from a fully intelligence-led approach: o Search rates showed substantial variation across the five sites that could not simply be explained by underlying crime rates o Overall, there was little relationship between the volumes of crime and searches over time, suggesting searches did not track in crime levels in away that might be expected with an intelligence-led approach. o Searches were spatially clustered in hotspots in the study sites. This clustering could not always be reduced to the volume of crime in those hotspots. Searches often seemed disproportionate to the underlying crime rate. o The locations where searches were geographical clustered were not consistently in those places where searches were most productive in terms of high arrest rates. o While search hotspots often coincided with crime hotspots, the match was less than perfect. Importantly, search hotspots sometimes appeared in places where recorded crime problems were not evident. At other times, crime hotspots emerged and persisted without the police concentrating their stop and search activity in the hotspots in response to the problem.

Download activity - last month

Export as XMLCSVJSON

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as CSVXMLJSON

Archive Staff Only

View Item