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Center for Text Analytic Methods in Legal Studies

Ashley, Kevin and Anderson, James and He, Daqing and Litman, Diane and Hwa, Rebecca (2022) Center for Text Analytic Methods in Legal Studies. In: Pitt Momentum Fund 2022.

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The Center for Text Analytic Methods in Legal Studies is a research collaboration of experts from the University of Pittsburgh’s Schools of Law and Computing and Information, the RAND Corporation, Duquesne Law School, and Worcester Polytechnic Institute. Their goal is to apply newly developed machine learning and natural language processing techniques to newly available sources of legal text data to evaluate legal and social questions involving racism, gender equality, immigration, public health, crime, or education that have real world policy implications and that traditionally have not been evaluable to the same extent without text analytic tools. Initially, the Center is investigating drug interdiction automobile stop cases concerning the constitutionality of police decisions to search. Such cases are a persistent cause of racial friction and have led to thousands of court decisions at the state and federal level. The team seeks to identify factors on which courts rely in assessing if police have “reasonable suspicion” to detain a motorist for further investigation (e.g., a police dog drug sniff), to assign statistical weights to these factors across thousands of cases, to identify explicit or implicit racial bias in the cases and explore their relationships to factor weights and case outcomes, and to draw out the social and legal policy implications of their findings.


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Item Type: Conference or Workshop Item (Other)
CreatorsEmailPitt UsernameORCID
Anderson, James
He, Daqingdah44@pitt.edu0000-0002-4645-8696
Centers: Other Centers, Institutes, Offices, or Units > Office of Sponsored Research > Pitt Momentum Fund
Date: 2022
Event Title: Pitt Momentum Fund 2022
Event Type: Other
DOI or Unique Handle: 10.18117/tk6h-fc80
Schools and Programs: School of Computing and Information > Computer Science
School of Computing and Information > Information Science
School of Law > Law
Refereed: No
Uncontrolled Keywords: Scaling Grants
Other ID: 5044
Date Deposited: 07 Mar 2022 19:55
Last Modified: 17 Feb 2023 20:16


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