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Estimation of Prevalence of Family-Related and Intimate Partner Femicides in Russia Using Text Analysis of Court Decisions
Sat, September 14, 8:00 to 9:15am, Faculty of Law, University of Bucharest, Floor: Ground floor, Amphitheater 3 „Mihail Eliescu”Abstract
In this research, we propose using texts of court verdicts as a potential source for estimating the prevalence of domestic and intimate partner femicides in Russia. The lack of a definition of gender-based violence in Russian law means that there are no reliable statistics available, and therefore the actual proportion of women murdered by their partners or family members in Russia is unknown. This makes it impossible to develop adequate policies for addressing the problem of domestic violence.
For our research, we collected all the available texts of court verdicts from 2011 to 2021 (N = 92,311). We obtained the texts by web scraping of two official websites: Mos-Gorsud.Ru, which contains cases heard by the Moscow City Court, and SudRF.Ru, which aggregates information from all other courts in the country (excluding the Moscow City Courts). We analyzed cases that fall under Article 105 (“Murder”), Article 107 (“Homicide Committed in a State of Temporary Insanity”), and Article 111 Part 4 (“Intentional Infliction of Grievous Bodily Harm Resulting in Death by Negligence”) of the Criminal Code of the Russian Federation. We used both rule-based techniques and machine learning to analyze the texts and identify relationships between the perpetrators and victims. The results showed that, on average, in each year from 2011 through 2019, 65% of female murders in Russia were committed by women’s partners or family members. Out of these family-related homicides, 81% were intimate partner homicides during this period. We also detected an increase in this proportion during the COVID-19 pandemic. In the years 2020–2021, these shares increased to 71% and 93%, respectively.
We conclude by discussing the limitations of using court verdicts as a source of data for empirical legal studies in general and the use of new computational methods in studying social problems.