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Towards a 'smart' cost-benefit tool: using machine learning to predict the costs of criminal justice policy interventions

Manning, Matthew; Wong, Gabriel; Graham, Timothy; Ranbaduge, Thilina; Christen, Peter; Taylor, Kerry; Wortley, Richard; Makkai, Toni; Skorich, Pierre


BACKGROUND: The Manning Cost–Benefit Tool (MCBT) was developed to assist criminal justice policymakers, policing organisations and crime prevention practitioners to assess the benefits of different interventions for reducing crime and to select those strategies that represent the greatest economic return on investment. DISCUSSION: A challenge with the MCBT and other cost–benefit tools is that users need to input, manually, a considerable amount of point-in-time data, a process that is time...[Show more]

CollectionsANU Research Publications
Date published: 2018-10-12
Type: Journal article
Source: Crime Science
DOI: 10.1186/s40163-018-0086-4
Access Rights: Open Access


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