ENGLISH

Using Modeling to Predict and Prevent Victimization

By Ken Pease , Andromachi Tseloni (auth.)

Book information

Publisher
Springer International Publishing
Year
2014
ISBN
978-3-319-03184-2, 978-3-319-03185-9
DOI
10.1007/978-3-319-03185-9
Language
english
Format
PDF
Filesize
5 MB (5561076 bytes)
Series
SpringerBriefs in Criminology 13
Edition
1
Pages
80\85
Time added
2014-02-12 18:00:00
and LawBehavorial ScienceCriminology & Criminal Justice; Statistics for SocEducationPublic Policy

Description

This work provides clear application of a new statistical modeling technique that can be used to recognize patterns in victimization and prevent repeat victimization. The history of crime prevention techniques range from offender-based, to environment/situation-based, to victim-based. The authors of this work have found more accurate ways to predict and prevent victimization using a statistical modeling, based around crime concentration and sub-group profiling with regard to crime vulnerability levels, to predict areas and individuals vulnerable to crime. Following from this prediction, they propose policing strategies to improve crime prevention based on these predictions. With a combination of immediate actions and longer-term research recommendations, this work will be of interest to researchers and policy makers in focused on crime prevention, police studies, victimology and statistical applications.

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