The panelists discuss the research project of judicial in-group bias in Indian criminal courts using a newly collected dataset on over 5 million criminal case records from 2010–2018. After detecting gender and religious identity using a neural-net classifier applied to judge and defendant names, the research exploits quasi-random assignment of cases to judges to examine whether defendant outcomes are affected by assignment to a judge with a similar identity. In the aggregate, the project estimates tight zero effects of in-group bias based on shared gender, religion, and last name (a proxy for caste). The researchers do find limited in-group bias in some (but not all) settings where identity is salient – in particular, they find a small religious in-group bias during Ramadan, and they find shared-name in-group bias when judge and defendant match on a rare last name.
Hosted in collaboration with the Mahbub ul Haq Research Centre (MHRC) as part of their Mahbub ul Haq Distinguished Lecture Series, the session was moderated by Dr. Ali Hasanain and Dr. Rabia Malik.