¡Vote Aqui! The Experiences and Motivations of Poll Worker Translators.
Published In: Social Science Quarterly (Wiley-Blackwell), 2025, v. 106, n. 2. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Lamb, Matt; Hostetter, Joshua D. 3 of 3
Abstract
Objective: First, we examine whether poll worker translators (PWTs) perceive state policies and election officials as hostile to their role during elections. Second, we consider the motivations why PWTs serve as poll workers. We consider three potential explanations for their service: civic duty and service to their community, solidarity and congregating with others, and material benefits such as financial compensation. Methods: We analyze the data from a web‐based survey of poll workers (n = 5771) in 19 counties within 10 states before the 2022 midterm election. The survey asked questions about poll worker responsibilities, including whether they provided translation services during the election (n = 134 PWTs). The survey also asked several questions about poll worker affect, motivations, and demographics. Results: PWTs are more likely to report that state laws make their job more difficult than poll workers who do not translate during an election. We also find that PWTs are more committed to voting rights than non‐PWTs. Conclusion: PWTs have more intrinsic motivations and self‐report more concerns related to state laws increasing the difficulty of being a poll worker. These insights may help inform the recruitment efforts of election administrators who need translation services in their culturally and linguistically diverse jurisdictions. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Social Science Quarterly (Wiley-Blackwell). 2025/03, Vol. 106, Issue 2, p1
- Document Type:Article
- Subject Area:Law
- Publication Date:2025
- ISSN:0038-4941
- DOI:10.1111/ssqu.70004
- Accession Number:183991296
- Copyright Statement:Copyright of Social Science Quarterly (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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