At Least Bias Is Bipartisan: A Meta-Analytic Comparison of Partisan Bias in Liberals and Conservatives

Ditto, PH; Liu, BS; Clark, CJ; Wojcik, SP; Chen, EE; Grady, RH; Celniker, JB; Zinger, JF

Abstract

Both liberals and conservatives accuse their political opponents of partisan bias, but is there empirical evidence that one side of the political aisle is indeed more biased than the other? To address this question, we meta-analyzed the results of 51 experimental studies, involving over 18,000 participants, that examined one form of partisan bias—the tendency to evaluate otherwise identical information more favorably when it supports one’s political beliefs or allegiances than when it challenges those beliefs or allegiances. Two hypotheses based on previous literature were tested: an asymmetry hypothesis (predicting greater partisan bias in conservatives than in liberals) and a symmetry hypothesis (predicting equal levels of partisan bias in liberals and conservatives). Mean overall partisan bias was robust (r = .245), and there was strong support for the symmetry hypothesis: Liberals (r = .235) and conservatives (r = .255) showed no difference in mean levels of bias across studies. Moderator analyses reveal this pattern to be consistent across a number of different methodological variations and political topics. Implications of the current findings for the ongoing ideological symmetry debate and the role of partisan bias in scientific discourse and political conflict are discussed.

Citation

Ditto, P., Liu, B., Clark, C., Wojcik, S., Chen, E., Grady, R., …Zinger, J. (2019). At Least Bias Is Bipartisan: A Meta-Analytic Comparison of Partisan Bias in Liberals and Conservatives. Perspectives on Psychological Science, 14(2), 273-291. https://doi.org/10.1177/1745691617746796

• Journal Article Type: Article
• Acceptance Date: Nov 10, 2017
• Online Publication Date: May 31, 2018
• Publication Date: Mar 1, 2019
• Deposit Date: Sep 21, 2018
• Publicly Available Date: Oct 18, 2018
• Journal: Perspectives on Psychological Science
• Print ISSN: 1745-6916
• Electronic ISSN: 1745-6924
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 2
• Pages: 273-291
• DOI: https://doi.org/10.1177/1745691617746796
• Public URL: https://durham-repository.worktribe.com/output/1348442