TY  - BOOK
AU  - Pease,Ken
AU  - Tseloni,Andromachi
ED  - SpringerLink (Online service)
TI  - Using Modeling to Predict and Prevent Victimization
T2  - SpringerBriefs in Criminology,
SN  - 9783319031859
AV  - HV6001-7220.5 
U1  - 364 23
PY  - 2014///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - social sciences
KW  - Statistics
KW  - Criminology
KW  - Social Sciences
KW  - Criminology & Criminal Justice
KW  - Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law
N1  - Introduction -- Crime Concentration -- Preventing Repeat Victimization -- Predicting Frequent Victimization -- Preventing Recurring Victimization -- Conclusions
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-319-03185-9
ER  -