Michael Rios
Michael Rios is the Data Scientist for the UCLA Voting Rights Project. He holds an MPP from UCLA Luskin School of Public Affairs and a B.A. in Political Science from UC Riverside. As a first-generation American, he uses data-driven research to understand disenfranchised communities and inform equitable policies. Michael analyzes population and voter datasets to identify trends and voting patterns, focusing on improving voting accessibility for individuals of color.
Utilizing Bayesian Improved Surname Geocoding (BSIG) to Explore California’s Diverse Electorate
Michael Rios’ presentation analyzed voter engagement in California’s 2022 Primary and General Elections, focusing on voters with disabilities, those requiring language assistance, and racial and ethnic groups. Voters with disabilities appreciated the convenience of vote-by-mail, though some requested larger text sizes and clearer polling site signage. Language assistance was primarily requested by older, non-English speakers, with lower turnout among those who received non-English ballots. Using Bayesian Improved Surname Geocoding (BISG), the analysis revealed turnout disparities, with White voters having the highest turnout. The findings emphasize the need for better accommodations and targeted outreach for underrepresented groups.
