Victim-Offender Overlap in Violent Crime: Targeting Crime Harm in a Canadian Suburb

Natalie Hiltz,Geoffrey C Barnes,Matthew Bland

doi:10.1007/s41887-020-00056-x

Abstract

Research QuestionTo what extent are victims of violent crime also offenders, and vice versa, with what concentrations of total crime harm across each person who has ever been reported as both a victim and an offender within the study period?DataWe analyse 27,233 unique individuals who were the subject of violent crime reports to the Peel Regional Police Service in Canada, either as offenders, victims, or both, for crimes reported between January 1, 2014, and December 31, 2016. Each individual linked to a violent crime in this period was tracked for the 730 days subsequent to the first crime report naming them.MethodsWe coded each crime with the Canadian Crime Severity Index (CCSI) to calculate victimization and offending harm totals across all incidents for each individual. We then computed each individual’s ratio of total CCSI from victimization to total CCSI from victimization. Based on the distribution of these ratios of CCSI from all offending to all victimization, we show how police can distinguish three categories of victim-offenders (VOs): predominant victims (PVs), predominant offenders (POs), and balanced victim-offenders (BVOs), as well as the single-category absolute offenders (AOs) and absolute victims (AVs).FindingsAcross all 27,233 individuals tracked, 17,138 (64%) appeared first as victims, and 10,095 (36%) appeared first as suspects. Of those appearing first as victims, 997 (6%) are linked to a violent crime as an offender within 730 days. Among those appearing first as offenders, 1019 (10%) are subsequently reported as victimized within 730 days. The total of this combined group (VOs) = 1665 individuals (6% of the entire population). Using a 3.5:1 ratio of victim to offender harm, we subdivide the 1665 VOs further into 322 predominant victims, 280 predominant offenders, and 1063 balanced victim-offenders. The 20% of individuals (n = 5455) with highest harm are linked to 71% of overall harm. On average, predominant offenders (who have also been victimized) are associated with 2.7 times as much harm as absolute offenders, and predominant victims (who have also been offenders) have three times as much harm as absolute victims.ConclusionsThis research shows how combining records of victimization and offending to target higher harm levels with greater potential benefits for police investments in harm reduction and prevention.

Highlights

Since Goldstein (1979) first identified problem-oriented policing as a quest for disrupting patterns of harm, a key question for policing has been how to set priorities across patterns. Sherman’s (2007: 313) discussion of the “power few” members of any group of police targets suggested the need for a precise metric of harm, if only to rankorder them for police intervention. Weinborn et al (2017) applied this metric for highharm places, as did Dudfield et al (2017) for high-harm victims, and Liggins et al (2019) for high-harm offenders.Yet other possibilities for targeting police resources may be found in combining two or more of these categories
Sandall et al (2018) have reported such an analysis across the categories of victims and offenders, showing that people who are identified in separate incidents as both victims and offenders have far greater harm scores than persons who are only victims or only offenders
This cut off can be described as follows: any victim-offender we identified whose victimization harm total was at least 3.5 times greater than their offending harm total was classified as a “predominant victim” (PV)

Summary

Introduction

Since Goldstein (1979) first identified problem-oriented policing as a quest for disrupting patterns of harm, a key question for policing has been how to set priorities across patterns. Sherman’s (2007: 313) discussion of the “power few” members of any group of police targets suggested the need for a precise metric of harm, if only to rankorder them for police intervention. Weinborn et al (2017) applied this metric for highharm places, as did Dudfield et al (2017) for high-harm victims, and Liggins et al (2019) for high-harm offenders.Yet other possibilities for targeting police resources may be found in combining two or more of these categories. Sandall et al (2018) have reported such an analysis across the categories of victims and offenders, showing that people who are identified in separate incidents as both victims and offenders have far greater harm scores than persons who are only victims or only offenders. This discovery opens further possibilities for simple classifications of crime patterns that police can understand in relation to setting priorities for resource allocation. Those possibilities logically extend to further parsing by harm levels of different categories within the population of victim-offenders

Methods

Results

Conclusion