George Karystianis, Nabila Chowdhury, Lorraine Sheridan, Sharon Reutens, Sunny Wade, Stephen Allnutt, Min-Taec Kim, Suzanne Poynton, Tony Butler
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引用次数: 0
Abstract
Background and setting
Domestic and family violence (DFV) is a significant societal problem that predominantly affects women and children. One behaviour that has been linked to DFV perpetration is coercive control. While various definitions have been proposed, it involves “acts of assault, threats, humiliation and intimidation or other abuse that is used to harm, punish, or frighten a victim” ranging from emotional to social and financial abuse. One potentially rich source of information on coercive control are police reports. In this paper we determine whether it is possible to automatically identify behaviours linked to coercive control from DFV police reports and present the prevalence of such behaviours by age and sex.
Methods
We modified an existing rule-based text mining method to identify 48 coercive control related behaviours from 406,196 DFV reports involving a single person of interest (POI) (i.e., an individual suspected or charged with a DFV offence) against a single victim from NSW Police Force records between 2009 and 2020.
Results
223,778 (54.6%) DFV events had at least one identifiable coercive control behaviour with the most common behaviour being verbal abuse (38.9%) followed by property damage (30.0%). Financial (3.2%) and social abuse (0.4%) were the least common behaviours linked to coercive control. No major differences were found in the proportion of DFV events between male and female POIs or victims. The oldest POI group (≥ 65 years) had the largest proportion for behaviours related to verbal abuse (38.0%) while the youngest POI group reported the highest proportion of DFV involving property damage (45.5%). The youngest victim group (< 18 years old) had the highest proportion of DFV events involving verbal abuse (37.3%) while victims between 18 and 24 years old reported the most harassment through phone calls and text messages (3.1% and 2.4% respectively); double that of those in the oldest (≥ 65 years) victim group (1.4% and 0.7% respectively).
Conclusions
Police data capture a wide variety of behaviours linked to coercive control, offering insights across the age spectrum and sex. Text mining can be used to retrieve such information. However, social and financial abuse were not commonly recorded emphasising the need to improve police training to encourage inquiring about such behaviours when attending DFV events.
期刊介绍:
Crime Science is an international, interdisciplinary, peer-reviewed journal with an applied focus. The journal''s main focus is on research articles and systematic reviews that reflect the growing cooperation among a variety of fields, including environmental criminology, economics, engineering, geography, public health, psychology, statistics and urban planning, on improving the detection, prevention and understanding of crime and disorder. Crime Science will publish theoretical articles that are relevant to the field, for example, approaches that integrate theories from different disciplines. The goal of the journal is to broaden the scientific base for the understanding, analysis and control of crime and disorder. It is aimed at researchers, practitioners and policy-makers with an interest in crime reduction. It will also publish short contributions on timely topics including crime patterns, technological advances for detection and prevention, and analytical techniques, and on the crime reduction applications of research from a wide range of fields. Crime Science publishes research articles, systematic reviews, short contributions and theoretical articles. While Crime Science uses the APA reference style, the journal welcomes submissions using alternative reference styles on a case-by-case basis.