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Classification errors in police statistics on criminal offenses with an extremist context

Publication at Central Library of Charles University, Faculty of Arts |
2021

Abstract

Police statistics serve as a basic tool for understanding the prevalence and nature of hate crimes, albeit with limited accuracy. This study focuses on statistics for crimes with an extremist context provided by the Czech police, which also includes bias crimes.

The aim is to ascertain the extent to which police statistics correspond to the information available to criminal justice authorities. Following existing research on hate crime statistics, the analysis maps classification error, i.e., a situation in which statistical data do not correspond to the information provided by criminal justice authorities.

A comparative analysis reveals that the number of bias crimes is higher than stated in police statistics and over half of the anti- Jewish, anti-Roma and anti-Muslim crimes are misclassified in terms of motive.