This study investigated gender differences in the perpetration of stalking violence and how sociocultural beliefs may account for these differences/similarities. A sample of 293 Australian undergraduate and postgraduate students classified as relational stalkers completed a selfreport questionnaire assessing violence perpetration (no/ moderate/severe violence) and sociocultural beliefs (justifications for relational violence; assessments of target fear). Female relational stalkers perpetrated elevated rates of moderate violence; however, there were no gender differences for severe violence. Both male and female relational stalkers were more supportive of justifications for femaleperpetrated relational violence than male-perpetrated relational violence. Violent male relational stalkers were more likely to believe they caused fear/harm than their female counterparts. These findings are interpreted in the context of sociocultural beliefs that view male-to-female violence as more unacceptable and harmful than female-to-male violence.
Purpose This paper aims to refine our understanding of life course offending patterns across gender and race/ethnicity and to advance work in this area by examining how gender and race/ethnicity interact to influence life course offending patterns. Methods We use criminal justice system data to construct a longitudinal offending cohort that includes all individuals born in 1983/1984 with at least one court finalization for a criminal offense in the state of Queensland between the ages of 10 and 25 years. The data include 41,280 offenders (25.6 % female; 8.9 % Indigenous Australian) responsible for 209,872 offenses (M=5.08, SD=12.31). Coupling these data with state-level census data for those born in 1983/1984 (N=129,782), we estimate cohort offending rates overall and disaggregated by gender and race/ethnicity both independently and jointly. Focusing on the offenders, we use semiparametric groupbased modeling to identify the number and longitudinal distributions of offending trajectories within the cohort and compare how subgroups defined by gender, Indigenous status, and their combination sort into these trajectories. Results Most of the birth cohort has little to no contact with the criminal justice system through age 25. However, patterns are not uniform across gender or race/ethnicity, with males and Indigenous Australians most likely to fit the serious and chronic offending trajectories. Gender and race/ethnicity also interact to influence offending patterns with non-Indigenous females significantly more likely than any other group to avoid system contact, while Indigenous males have comparatively exaggerated rates of contact. Moreover, Indigenous females offend in ways more similar to non-Indigenous males than females and, in some instances, evidence even more serious offending. J Dev Life Course Criminology (2015) Conclusions Developmental and life course models should highlight not just the operant developmental dynamics across key life stages or the relevant age-graded risk and protective factors at play, but also how gender and race/ethnicity condition these processes both independently and jointly.
This study assessed the longitudinal costs of offender trajectories in Queensland (Australia) to provide policymakers with evidence that could be used to promote the use of crime prevention programs. Few studies have assessed these costs and minimal research has been conducted outside the United States. The study addressed three research questions: (1) What are the monetary costs of crime? (2) What is the optimal number of offender trajectories in an Australian offender cohort? and (3) What are the monetary costs of officially recorded offending for individuals on different offender trajectories? The Semi-Parametric Group-based Method (SPGM) was used to determine the number of offender trajectories in the Queensland Longitudinal Database. This database included 41,377 individuals who were born in 1983 and 1984 and guilty of offences in Queensland that were committed when aged 10 to 25 years old. The costs of crime were assessed using two approaches. First, criminal justice system costs were estimated based on the number and type of contacts that individuals had with the criminal justice system as well as the length of any supervision served. Second, wider social and economic costs were assessed based on offence type. Results indicated that there were five offender trajectories, including two chronic, one moderate and two low trajectories. When costs were applied to the offender trajectories, offenders in the two chronic groups were 4.8% of the cohort but accounted for 41.1% of the total costs. On average, each chronic offender cost between $186,366 and $262,799 by the time they turned 26 years old, with 60% of the costs accounted for by the criminal justice system. On average, each chronic offender cost over 20 times more than offenders in the two low offending groups. These findings provide further evidence for the potential benefits of implementing interventions that target chronic offenders.
A fundamental challenge to developmental and life-course (DLC) criminology research is access to appropriate longitudinal data to examine hypotheses concerning causal risk factors for offending and within-individual change over time, and to empirically test DLC theories. In this paper we present a powerful method for collecting appropriate data – linked administrative data. The Queensland Linkage Project includes three population-based longitudinal linked administrative databases – the Queensland Longitudinal Data (QLD) – QLD 83, QLD 84 and QLD 90. We describe the methodology of linking administrative data, the establishment of the QLD datasets and a selection of the work facilitated by these data. This work addresses issues raised by the editors including the effects of life events and the timing of risk factors (child maltreatment) on further offending, the monetary costs of offending across the life-course and the development of adult-onset offending. We finish by describing current work on the Queensland Linkage Project where mental health system data are being integrated with justice system data.
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