Report
Crime by outlaw motorcycle gang members during club conflicts
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.
Report
Predicting high-harm offending using machine learning: an application to outlaw motorcycle gangs
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...
Report
Predicting prolific live streaming of child sexual abuse
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...
Report
Effective management of serious police misconduct: a machine learning analysis
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.
Report
Effects of outlaw motorcycle gang membership and the support needs of former members
Drawing on interviews with 39 former members of outlaw motorcycle gangs, this research identifies consequences associated with leaving the club and the effects of membership experienced before and after leaving.