Skip navigation
Skip navigation

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

Description

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
URI: http://hdl.handle.net/1885/206620
Source: Crime Science
DOI: 10.1186/s40163-018-0086-4
Access Rights: Open Access

Download

File Description SizeFormat Image
01_Manning_Towards_a_%27smart%27_cost-benefit_2018.pdf1.29 MBAdobe PDFThumbnail


This item is licensed under a Creative Commons License Creative Commons

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator