In this paper, the authors explore the prevalence and patterns of recorded domestic violence offending among outlaw motorcycle gang (OMCG) members in New South Wales. They then compare domestic violence offending among a sample of OMCG members and other male offenders who committed their first recorded offence in the same year.

This study examines the trends in and spatial distribution of recorded offending by Australian outlaw motorcycle gang (OMCG) affiliates at the onset of a territorial conflict between two clubs in the state of New South Wales.

The nature of offending by outlaw motorcycle gangs (OMCGs), and policing responses, requires a novel approach to risk assessment. This study uses machine learning methods to develop a risk assessment tool to predict recorded high-harm offending. Results are compared with those of a model predicting any recorded offending.

Technologically-enabled crime has proliferated in recent years. One such crime type is the live streaming of child sexual abuse (CSA). This study employs a machine learning approach to better understand the characteristics of Australians who engaged with known facilitators of CSA live streaming in the Philippines.

There are a range of management strategies available to police agencies to prevent serious misconduct. This study uses partial dependence plots to explore management strategies which have been identified as either increasing or decreasing risk of serious police misconduct.