At Least Bias Is Bipartisan: A Meta-Analytic Comparison of Partisan Bias in Liberals and Conservatives
Open accessAbstract
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.
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All of these mechanisms, sometimes grouped under 'myside bias', can contribute to issue polarization, insofar as individuals often become more extreme in their opinions after selectively processing the evidence on specific topics such as capital punishment, immigration, healthcare policy or climate change.
“All of these mechanisms, which are sometimes grouped under the general rubric of ‘myside bias’111–113, can contribute to issue polarization, insofar as individuals often become more extreme in their opinions after selectively processing the evidence on specific topics such as capital punishment, immigration, healthcare policy or climate change114,115.”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [115]
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Experimental — accuracy not yet measuredPeople may evaluate the same information more favourably when it supports (versus contradicts) the beliefs, opinions and values of one's political in-group.
“For example, people may evaluate the same information more favourably when it supports (versus contradicts) the beliefs, opinions and values of one’s political in-group103,115,120.”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [115]
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Self-citation
- Authors
- Ditto, P. H., Liu, B. S., Clark, C. J., Wojcik, S. P., Chen, E. E., Grady, R. H., Celniker, J. B., & Zinger, J. F.
- Affiliations
- University of California, Irvine (US)
- Kalamazoo College (US)
- Florida State University (US)
- Corresponding author
- Ditto, Peter H.
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2018-05-31
- Volume
- 14
- Issue
- 2
- Pages
- 273-291
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- OpenAlex
- W2611901353
- Cited by
- 535
- References
- 17
- Citations by year
- 2026: 64 · 2025: 44 · 2024: 70 · 2023: 86 · 2022: 71 · 2021: 78 · 2020: 71 · 2019: 40 · 2018: 11
- FWCI
- 113.80
- Type
- journal article
- Language
- en
- Open access
- Locations
- Perspectives on Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Durham Research Online (Durham University) (acceptedVersion, other-oa)
- Durham Research Online (Durham University) (submittedVersion, cc-by)
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Political Science and International Relations › Academic Freedom and Politics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Keywords
- partisan bias, liberals, conservatives, political ideology, confirmation bias, information evaluation, political conflict, scientific discourse
- MeSH terms
- Group Processes, Humans, Motivation, Politics, Prejudice, Thinking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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