Rethinking the concept of punishment: modeling the level of danger posed by criminals to society

Abstract

The rapid increase in crime rates in many countries is evidence of the ineffectiveness of the current punishment system and the need to rethink the existing approach to applying punitive sanctions to criminals, taking into account the threat they pose to others. This study aims to build an analytical model for an objective assessment of the level of danger posed by suspects (convicts/prisoners) to society, based on their socio-demographic characteristics and data on previous criminal activity. To achieve this goal, discriminant canonical analysis is used as a multivariate statistical method for classifying objects. The empirical base consisted of data on 13,010 convicts serving sentences in penitentiary institutions in Ukraine. Key factors that have a significant impact on the distribution of criminals into groups (high, moderate, low) according to the level of danger they pose to society have been identified: the age at which a person was first sentenced, early dismissals, suspended convictions, education level, type of employment, the motivation for dismissal. An optimal canonical discriminant model has been constructed that allows for the accurate classification of new cases into the identified groups. The results obtained can be used in the judicial system, probation services, and law enforcement agencies to make informed decisions regarding the measure of punishment, parole, level of supervision, and ensuring public safety. The proposed applied solution can be integrated into an automated analytical system to increase the efficiency of the judicial system.