Reducing domestic abuse by improving the measurement and analysis of data on domestic abuse

• In Event: WCCJ Panel 8 – Measurement and Technology in Domestic Abuse

Abstract

Reliable and valid measures of domestic abuse (DA) at the individual, neighbourhood, regional and national levels are crucial. A clear understanding of the nature and extent of the problem will allow us to respond appropriately to reduce levels of DA, reduce harm resulting from DA, and protect lives. A number of sources of information are available, each with their own strengths but each with considerable weaknesses. One source that is little used but shows promise is data from regional police force information systems. This data contains information on all incidences that come to the attention of the police including information on the victim as well as the offender. It also includes data on referrals and crime reports to provide vital context. A study that examines the complex patterns of victim/offender status and relationship between victim and offender will be presented. The study is based on analysis of structured police data and demonstrates the potential of this data for measuring and understanding DA and particularly the multi-dimensionality of repetition. This paper will explain how this analysis could be further improved by incorporating the results of Natural Language Processing of the free text from crime reports. However, despite the promise shown by this data, there are a number of issues that affect its value. For instance, each force only records information on incidences and crimes that occur within their own boundaries. Ongoing work by the author and colleagues in the VISION consortium will address such issues. The main aim of the VISION consortium - a five-year national project funded by a £7million grant from the UKPRP – is to optimise and synthesise fragmented data on all forms of violence from multiple sources (police, surveys, courts, health etc) within a shared framework. I will close by outlining this work and what we will achieve.

Author

• Leslie Humphreys, University of Central Lancashire