Abstract

This paper presents a typology of male domestic violence offenders in Kazakhstan using a sequence analysis approach. In 2023, more than 99,000 complaints of domestic violence were recorded by law enforcement agencies, and in 2024 this number exceeded 100,000. Despite the scale of the problem, longitudinal patterns of offending and the structure of offenders’ trajectories remain insufficiently studied.

The analysis draws on unique administrative records of domestic violence-related offenses from January 2020 to July 2024, provided by the Committee on Legal Statistics and Special Accounts of the Prosecutor General’s Office of the Republic of Kazakhstan. The study focuses on male offenders and does not include information on the relationship between offenders and victims.

The research applies life-course criminology to conceptualize offending as a dynamic process unfolding over time. Sequence analysis is used to reconstruct ordered histories of administrative offenses and to identify distinct trajectory types. The study is designed to compare three groups: (1) offenders involved in domestic violence, (2) repeat offenders in domestic violence, and (3) offenders without such incidents.

Preliminary results for repeat offenders reveal stable combinations of domestic violence, child-related offenses, traffic violations, and alcohol-related incidents. Four trajectory types are identified: “specialists” in domestic violence, “specialists” in child-related offenses, “versatile” offenders, and offenders with sporadic incidents. Comparative analysis across groups will clarify how these patterns differ depending on involvement in domestic violence.

The findings demonstrate that sequence-based typologies can capture qualitative differences in offending trajectories beyond frequency measures. The study contributes to understanding offender heterogeneity and provides a basis for identifying risk groups and developing prevention strategies in the context of administrative regulation of domestic violence in Kazakhstan.

Key words: domestic violence, male offenders, law enforcement data, Kazakhstan, sequence analysis