Investigating the Dynamics of Outlaw Motorcycle Gang Co-Offending Networks: The Utility of Relational Hyper Event Models

Abstract Objectives Approaches to the study of Outlaw Motorcycle Gangs OMCGs tend focus on offending at individual level, with limited nature and extent co-offending among these affiliates. We aim examine by using relational hyper event models (RHEM) determine what additional insights can be discerned above beyond more traditional network approaches. Methods Using de-identified police recorded incident data for affiliates in New South Wales, Australia, including their rank club affiliation, we examined positioning OMCG structures. The comprised 2,364 nodes 12,564 arrest events. argue that Relational Hyperevent Models are optimal analytical strategy as it overcomes some limitations analyses. Results conducted RHEM modelling found networks were stable over time, whereby actors tended repeatedly co-offend same partners. Lower ranked members likely engage compared office bearers. Conclusions provide support scenario which operate criminal organisations, but also protection distance from is afforded review implications results law enforcement policy practice scholarship OMCGs.