Panel: How Machine Learning Can or Cannot Improve Policy Studies
(Methods and Tools of Analysis)

Friday, November 8, 2019: 1:30 PM-3:00 PM
Plaza Building: Concourse Level, Governor's Square 15 (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Panel Chair:  Johannes Himmelreich, Syracuse University
Discussant:  Richard Hendra, MDRC

How Machine Learning Can or Cannot Improve Policy Studies


Within-Population Occupational Segregation By Ethnicity during the Age of Mass Migration: A Machine Learning Approach
Yuxin Zhang, University of Texas, Austin and Dafeng Xu, University of Washington



Combining Family History and Machine Learning to Link Historical Records
Joseph Price1, Kasey Buckles2, Isaac Riley1 and Jacob Van Leeuwen1, (1)Brigham Young University, (2)University of Notre Dame



Comparing Manual Qualitative Coding to Natural Language Processing: A Case Study of Financial Decision-Making
Anna Jefferson, Siobhan Mills, Xi Xi and Meaghan Hunt, Abt Associates, Inc.




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