Journal article
Demographic differences in understanding and utilization of ranked choice voting
Social science quarterly, Vol.103(7), pp.1539-1550
12/2022
DOI: 10.1111/ssqu.13215
Appears in UI Libraries Support Open Access
Abstract
Objectives New York City is the largest U.S. jurisdiction to use ranked choice voting (RCV). We examine New York and other U.S. cities using RCV to assess if there were different levels of understanding and utilization of RCV across demographic groups. Methods We placed items on a survey conducted during the 2021 New York City RCV election that had been included in two previous surveys of different U.S. cities using RCV. Results We find higher levels of reported understanding and rates of ranking multiple candidates in NYC than in other jurisdictions. We find no systematic differences by race/ethnicity in terms of reported understanding of RCV in NYC or the other samples. We also find no systematic association between age and reported understanding of RCV. Respondents with more education were more likely to report understanding RCV in each sample. People of color were less likely to report ranking multiple mayoral candidates in NYC and California, and respondents with more education were more likely to report ranking in two samples. Conclusions Apart from these important differences in utilization, our search for race/ethnic differences largely produced null results, suggesting RCV may not produce bias in who engages with it.
Details
- Title: Subtitle
- Demographic differences in understanding and utilization of ranked choice voting
- Creators
- Todd Donovan - Western Washington UniversityCaroline Tolbert - University of IowaSamuel Harper - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Social science quarterly, Vol.103(7), pp.1539-1550
- DOI
- 10.1111/ssqu.13215
- ISSN
- 0038-4941
- eISSN
- 1540-6237
- Publisher
- Wiley
- Number of pages
- 22
- Language
- English
- Electronic publication date
- 10/19/2022
- Date published
- 12/2022
- Academic Unit
- Center for Social Science Innovation; Public Policy Center (Archive); Political Science
- Record Identifier
- 9984323338502771
Metrics
31 Record Views