Partisan Antipathy and the Erosion of Democratic Norms
Open accessAbstract
Does partisan antipathy undermine democracy? Over the past decade, claims of such an effect have pervaded both popular and scholarly discourse—to the point where the link has become widely accepted as an article of faith. But an impressive stream of new studies has raised credible doubts about whether such an effect actually exists. In the present report, even as we replicate the null effects in that nascent literature, we demonstrate that partisan antipathy, when properly conceptualized and operationalized, does indeed predict antidemocratic tendencies. Leveraging cross-sectional, longitudinal, and experimental methods, including a study conducted during America’s 2022 Midterm Elections, we developed and validated a measure of political sectarianism (a blend of othering, aversion, and moralization toward opposing partisans), which robustly predicted antidemocratic tendencies. In contrast, the influential construct of affective polarization (assessed in terms of cold feelings toward opposing partisans) did not. These findings have important implications for theory and measurement in the social sciences, for understanding democratic erosion, and for applied efforts to bolster American democracy by bridging partisan divides.
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Changes in affective polarization are not necessarily linked to changes in antidemocratic attitudes.
“These results are consistent with recent studies finding that changes in affective polarization are not necessarily linked to changes in antidemocratic attitudes (39,50).”
From Reranking partisan animosity in algorithmic social media feeds alters affective polarization (2025) · cites this paper as [50]
These findings align with recent studies which have observed that affective polarization is not robustly linked to antidemocratic tendencies.
“These findings also align with recent studies which have observed that affective polarization is not robustly linked to antidemocratic tendencies (50).”
From Reranking partisan animosity in algorithmic social media feeds alters affective polarization (2025) · cites this paper as [50]
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Reranking partisan animosity in algorithmic social media feeds alters affective polarization
Piccardi, T., Saveski, M., Jia, C., Hancock, J., Tsai, J. L., & Bernstein, M. S. (2025) · Science · doi:10.1126/science.adu5584 · Cited by 34 · see citing works
Measuring affective polarization: Matching concepts to measures
Druckman, J. N., Klar, S., Krupnikov, Y., Levendusky, M., & Ryan, J. B. (2026) · Political Psychology · doi:10.1111/pops.70152 · Cited by 1 · see citing works
Self-citation
- Authors
- Landry, A., Finkel, E., Hoyle, R. H., Druckman, J., & Van Bavel, J. J.
- Affiliations
- Northwestern University (US)
- Publisher
- Center for Open Science
- Published
- 2024-01-25
- OpenAlex
- W4391228217
- Cited by
- 10
- References
- 5
- Citations by year
- 2026: 7 · 2025: 3
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- PsyArXiv (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Social Sciences › Political Science and International Relations › Political Theory and Democracy
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Keywords
- sectarian politics, affective polarization, democratic backsliding, othering, moralization, 2022 midterm elections, partisan divide, democratic norms
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