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Approaches to outlaw motorcycle gangs in the Netherlands and Australia
Episode 2210th December 2021 • OC24 Podcast • Global Initiative Against Transnational Organized Crime
00:00:00 01:12:04

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Shownotes

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.

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 behavioural changes in outlaw bikers, or whether they result from changes in police practices.

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.

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

NSCR, Australian Institute of Criminology, Australian Institute of Criminology.



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Chartable - https://chartable.com/privacy

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