Anthony Morgan Arjan Blokland Teun van Ruitenburg Christian Klement Timothy Cubitt

Approaches to outlaw motorcycle gangs in the Netherlands and Australia

A Talk by Arjan Blokland , Timothy Cubitt , Christian Klement , Anthony Morgan and Teun van Ruitenburg

About this Talk

  1. Teun van Ruitenburg - Raising Barriers to Outlaw Motorcycle Gangs in The Netherlands

In this empirical study, the author shows that the Dutch approach to outlaw motorcycle gangs (OMCGs) has made a 180-degree shift from inclusion in the 1970s to exclusion in present times. Based on interviews with 76 respondents working for different law enforcement agencies and an analysis of (internal) policy documentation, this presentation will focus on how the Dutch government since 2012 is raising barriers to OMCGs using Administrative, Civil, Fiscal and Criminal Law. In doing so, it is demonstrated that today’s efforts to fight OMCGs must not be solely explained by the attempt to reduce crime.

  1. Christian Klement & Arjan Blokland - Preventing outlaw biker crime in the Netherlands or just changing the dark figure of crime?

In the presented study, we estimate effects of the Dutch whole-of-government approach to outlaw biker crime. We do so by applying interrupted time series analysis to crime records on 1617 OMCG members and 473 support club members. Although caveats remain, results indicate that the approach has an effect on criminal involvement, but that it depends on crime type and subsample in question. Overall crime seems unaffected, whereas organized crime is shown to decrease. We discuss whether the effects are due to behavioral changes in outlaw bikers, or whether they result from changes in police practices.

  1. Timothy Cubitt & Anthony Morgan - Predicting high-harm offending using machine learning: An application to Australian outlaw motorcycle gangs

Despite growing recognition that certain OMCG members and their clubs are more likely to be involved in serious crime, this is not an area where risk assessment tools have been developed and validated. This study uses machine learning methods to develop a risk assessment to predict recorded high-harm offending among 2,246 OMCG members in New South Wales. Results showed the model predicted high-harm offending with a high degree of accuracy. Importantly, the tool appeared able to accurately identify offenders prior to the point of escalation, and can be used to help inform law enforcement responses.

About The Speakers

Say hello to your Speakers for this Talk.

Arjan Blokland

Arjan Blokland


Criminal careers, criminal networks, outlaw motorcycle gangs

Timothy Cubitt

Timothy Cubitt

Principal Research Analyst, Australian Institute of Criminology

Tim is a Principal Research Analyst at the Australian Institute of Criminology. He leads research considering Outlaw Motorcycle Gangs, countering violent extremism, police misconduct and the online exploitation of children.

Christian Klement

Christian Klement

Anthony Morgan

Anthony Morgan

Australian Institute of Criminology

Manages the Australian Institute of Criminology’s Serious and Organised Crime Research Lab

Teun van Ruitenburg

Teun van Ruitenburg

Netherlands Institute for the Study of Crime and Law Enforcement

Postdoctoral Researcher

Categories Covered

criminal governance



regular panel