This report is a result of a project which aims to illustrate some of the ways in which police-recorded crime data could be combined with other sources to provide a deeper insight into the geographical and social distribution of violent crime.
Generating evidence on the nature and distribution of violent crime, and what can be done about it, is a key problem currently facing police. While police-recorded data can offer important insights, it only captures part of the picture of violent crime. While we often reflect on what crimes are committed, we may think less about where or when they occur, or why. Combining police data with other sources offers us the potential to address some of these limitations, and maximise the utility of data collection and analysis strategies.In Violent crime in London: trends, trajectories and neighbourhoods we set out to illustrate some of the ways combining different data sources might provide deeper insight into the geographical and social distribution of violent crime. In addition to merging datasets, we prioritised the use of robust analysis techniques. We used three different approaches – mapping, predictive models and trajectory models – to consider the patterning of police-recorded violent crime across London; and we used a novel machine learning technique to assess the potential impact of stop and search on crime.Crime mapping provided the baseline analysis. Using crime data from London across five financial years (2013-2017), we aggregated annual counts of violent crime to the LSOA level (Lower-level Super Output Areas are a Census-based area level classification, with an average population size of around 1,500 people – there are 4,835 LSOAs in Greater London). These maps revealed the stark geographical clustering of violent crime, concentrated in a small number of LSOAs distributed across the capital.
Police organisations will of course have access to much more detailed and fine-grained data, which could be used to increase the resolution of the analysis, evaluate specific policy interventions, and so on. Resources like the UCL Jill Dando Institute Research Laboratory (JDIRL), which we used when doing this research, may thus become increasingly important. The JDIRL is a secure computer facility that allows authorised access to sensitive datasets that would not otherwise be accessible. As analysis of complex datasets becomes increasingly important to policing, offering access to academics and other researchers should provide significant benefits in terms of the breadth, depth and utility of the outputs generated.
The full report was prepared for the College of Policing by Dr Alex Sutherland (Behavioural Insights Team); Professor Ian Brunton-Smith (University of Surrey); Oli Hutt and Professor Ben Bradford (University College London)
This report was prepared as part of
the Vulnerability and Violent Crime Programme. The Phase
2 intervention evaluations will be published in Spring
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