Domestic violence and abuse (DVA) is repetitious, and much of the demand is attributable to repeat victims and perpetrators. Targeting resources at repetition could be an effective method of reducing demand. Targeting repetition requires accurate information on repeat victims and perpetrators. This thesis uses data from Lancashire Constabulary to investigate: what data do the police have on DVA; what are the problems with the current structure of police data for measuring DVA repetition; how can police data be improved to measure DVA repetition?
Analysis of existing police datasets found the data unsuitable for measuring DVA repetition for four key reasons: different units of measurement; inconsistent recording of personal details; misuse of DVA markers; and information lost in free-text. The framework for measuring DVA repetition and assessing police interventions, was derived from the DVA literature. Observations of the response mapped out the complexity and identified relevant data sources. Information from multiple sources was recoded into a new dataset following the measurement framework.
The new dataset estimated that 51% of victims were repeats, compared to 21% in the original crime dataset. A series of analyses were conducted, designed around existing debates in the DVA literature, for instance whether DVA is gendered and escalatory. The analysis demonstrated the potential for police data to measure patterns of DVA repetition, and assess the impact of police action.
The thesis contributes a process map of the police response to DVA; a measurement framework for measuring DVA and assessing police actions; criteria for future police data collection; and a methodology for restructuring police data. Though the outputs are methodological, the thesis is driven by the substantive implications of improved police data on the ability of the police to measure, respond to and reduce DVA. The thesis has implications for police practice, policy, and Criminological theory.