Gender-Based Ingroup Bias in the Application of Belgian Asylum Law
Impartiality is a central goal of the judiciary. However, a body of literature documented that judges often exhibit bias in decision-making. In the context of asylum adjudication, evidence of disparities in decision-making is also apparent. While the existing "refugee roulette" literature mainly focuses on the relationship between the judge's or the refugee's gender and the asylum decision, the impact of same-gender judge-refugee pairings on asylum appeal outcomes only received limited attention. This paper studies the existence of gender-based ingroup bias in Belgian asylum appeals by examini... Mehr ...
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Dokumenttyp: | conferenceObject |
Erscheinungsdatum: | 2023 |
Schlagwörter: | Judicial bias / Gender / Ingroup bias / Asylum appeals |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26529468 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/1942/40246 |
Impartiality is a central goal of the judiciary. However, a body of literature documented that judges often exhibit bias in decision-making. In the context of asylum adjudication, evidence of disparities in decision-making is also apparent. While the existing "refugee roulette" literature mainly focuses on the relationship between the judge's or the refugee's gender and the asylum decision, the impact of same-gender judge-refugee pairings on asylum appeal outcomes only received limited attention. This paper studies the existence of gender-based ingroup bias in Belgian asylum appeals by examining a novel dataset of 23,248 verdicts of the Belgian Council for Alien Law Litigation. Using a difference-indifference approach, we show that a judge-refugee gender match results in significantly higher chances for the refugee of receiving a favorable decision (about 35% from the mean value of a favorable decision for a refugee). In addition, we also provide evidence that ingroup bias is more pronounced in verdicts in which asylum authorities more strongly contest asylum narrative credibility, which we quantify by estimating a structural topic model, a state-of-the-art machine learning method. This paper is one of the first to examine gender-based ingroup bias in asylum appeals. This is a high-stakes context because of the direct and far-reaching consequences of the decision for the asylum seeker. The findings of positive gender-based ingroup bias are of direct interest to policymakers in creating awareness about the consequences of refugee-judge gender pairings within asylum courts.