What to Do with Vast Amounts of Detailed Data in Quantitative Sentencing Research? Approaches to Grouping Criminal Behaviors for Sentencing Analyses

• In Event: Re-thinking sentencing research: new possibilities and new approaches

Abstract

Quantitative sentencing research has long grappled with the challenge of using insufficiently detailed data in analyses. However, with the increasing availability of new data sources on criminal behavior, a new problem emerges: how to effectively handle highly detailed information about offenses. This issue is particularly evident when using digitalized court verdicts, which provide previously unavailable details about criminal behavior. While these data offer valuable insights, they also raise a key challenge: how to systematically group similar behaviors to construct detailed models that account for individual factors and sentencing disparities. The traditional categorization of crimes into property, drug-related, or violent offenses lacks sufficient granularity, limiting the potential of these rich datasets when such coarse categorization is applied. In this presentation, I propose principles for developing a more refined classification of criminal behaviors that enable a more precise analysis of sentencing disparities and the influence of specific offense characteristics.

Author

• Jakub Drápal, Charles University; Institute of State and Law of Czech Academy of Sciences