JOURNAL ARTICLE
Public perceptions of pollsters in the United States: Experimental evidence.
Published In: Social Science Quarterly (Wiley-Blackwell), 2024, v. 105, n. 1. P. 114 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Johnson, Timothy P.; Silber, Henning; Darling, Jill E. 3 of 3
Abstract
Objective: Anecdotal evidence suggests that the term "pollster" has, in recent years, become stigmatized in the United States. We explore this and a subsequent question as to whether negative perceptions of pollsters affect people's perceived trustworthiness of survey findings. Methods: Survey experiments were administered to national probability‐based samples after the 2016 and 2020 elections. Results: In each study, pollsters obtained significantly more negative ratings when compared to "survey researchers" and "public opinion researchers," suggesting that the general public views pollsters, who are more likely to be viewed as partisan, as being less honest/ethical. In line with social identity theory, interaction models revealed that those rating pollster critic Donald Trump most favorably had the most negative ratings of pollsters and public opinion researchers, compared to survey researchers. Yet, the vignette experiment showed that negative perceptions of pollsters did not affect the perceived trustworthiness of survey result reports. Conclusions: We conclude that while there appears to be a stigmatization of pollsters, those negative perceptions do not translate into less trust in the findings of public opinion. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Social Science Quarterly (Wiley-Blackwell). 2024/01, Vol. 105, Issue 1, p114
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2024
- ISSN:0038-4941
- DOI:10.1111/ssqu.13324
- Accession Number:175230230
- 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.