A machine learning analysis of serious misconduct among Australian police

IF 3.1 Q1 CRIMINOLOGY & PENOLOGY

Crime Science Pub Date : 2020-10-31 DOI:10.1186/s40163-020-00133-6

Timothy I. C. Cubitt, K. Wooden, K. Roberts

引用次数: 10

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对澳大利亚警方严重不当行为的机器学习分析

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Crime Science Social Sciences-Cultural Studies

CiteScore

11.90

自引率

8.20%

发文量

审稿时长

13 weeks

期刊介绍： Crime Science is an international, interdisciplinary, peer-reviewed journal with an applied focus. The journal''s main focus is on research articles and systematic reviews that reflect the growing cooperation among a variety of fields, including environmental criminology, economics, engineering, geography, public health, psychology, statistics and urban planning, on improving the detection, prevention and understanding of crime and disorder. Crime Science will publish theoretical articles that are relevant to the field, for example, approaches that integrate theories from different disciplines. The goal of the journal is to broaden the scientific base for the understanding, analysis and control of crime and disorder. It is aimed at researchers, practitioners and policy-makers with an interest in crime reduction. It will also publish short contributions on timely topics including crime patterns, technological advances for detection and prevention, and analytical techniques, and on the crime reduction applications of research from a wide range of fields. Crime Science publishes research articles, systematic reviews, short contributions and theoretical articles. While Crime Science uses the APA reference style, the journal welcomes submissions using alternative reference styles on a case-by-case basis.