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A0789
Title: The impact of MeToo on language at court: A text-based causal inference approach Authors:  Henrika Langen - University of Fribourg (Switzerland) [presenting]
Abstract: This study assesses the effect of the MeToo movement on different quantifiers of the 2015-2020 judicial opinions in sexual violence-related cases from 62 U.S. courts. The judicial opinions are vectorized into bag-of-words and tf-idf vectors in order to study their development over time. Further, different indicators quantify to what extent the judges use a language that implicitly shifts some blame from the victim(s) to the perpetrator(s). These indicators measure how the grammatical structure, the sentiment and the context of sentences mentioning the victim(s) and/or perpetrator(s) change over time. The causal effect of the MeToo movement is estimated by means of Difference-in-Differences comparing the development of the language in opinions on sexual violence and other interpersonal crime-related cases as well as by applying panel event study analysis. The results point at a change in the language at court induced by the MeToo movement which materializes with a substantial time lag. Further, the study considers potential effect heterogeneity with respect to the judges' gender and his/her political affiliation. The study combines causal inference with text quantification methods that are commonly used for classification as well as with indicators from the fields of sentiment analysis, word embedding models and grammatical tagging.