Cited by 54Social and Intergroup PsychologyElectoral Systems and Political ParticipationMedia Influence and Politics

The objectivity illusion and voter polarization in the 2016 presidential election

Open access
Schwalbe, Michael C., Cohen, Geoffrey L., Ross, Lee D.·2020·Proceedings of the National Academy of Sciences

Abstract

Significance: Political polarization increasingly threatens democratic institutions. The belief that “my side” sees the world objectively while the “other side” sees it through the lens of its biases contributes to this political polarization and accompanying animus and distrust. This conviction, known as the “objectivity illusion,” was strong and persistent among Trump and Clinton supporters in the weeks before the 2016 presidential election. We show that the objectivity illusion predicts subsequent bias and polarization, including heightened partisanship over the presidential debates. A follow-up study showed that both groups impugned the objectivity of a putative blog author supporting the opposition candidate and saw supporters of that opposing candidate as evil.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.1912301117

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Individuals assume, in a self-serving manner, that they process information in a more rational, impartial and accurate way than others do (naive realism and objectivity illusion).

    “Closely related to the phenomenon of myside bias are ‘naive realism’ and the objectivity illusion, whereby individuals assume, in a self-serving manner, that they process information in a more rational, impartial and accurate way than others do120.”
  • People 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.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 23

  1. [1]Fiske S. T., Social cognition and social perception. Annu. Rev. Psychol. 44, 155– 194 (1993). 8434891
  2. [2]Berlin I., Concepts and Categories: Philosophical Essays, (Princeton University Press, Princeton, NJ, 2013).
  3. [3]Sapolsky R. M., Behave: The Biology of Humans at Our Best and Worst, (Penguin, New York, NY, 2017).
  4. [10]Abramowitz A. I., Saunders K. L., Is polarization a myth? J. Polit. 70, 542– 555 (2008).
  5. [12]Hochschild A. R., Strangers in Their Own Land: Anger and Mourning on the American Right, (The New Press, New York, NY, 2016).
  6. [13]McCarty N., Poole K. T., Rosenthal H., Polarized America: The Dance of Ideology and Unequal Riches, (MIT Press, Cambridge, MA, 2006).
  7. [14]Sunstein C. R., Republic: Divided Democracy in the Age of Social Media, (Princeton University Press, Princeton, NJ, 2018).
  8. [18]Ehrlinger J., Gilovich T., Ross L., Peering into the bias blind spot: People’s assessments of bias in themselves and others. Pers. Soc. Psychol. Bull. 31, 680– 692 (2005). 15802662
  9. [24]Chambers J. R., Melnyk D., Why do I hate thee? Conflict misperceptions and intergroup mistrust. Pers. Soc. Psychol. Bull. 32, 1295– 1311 (2006). 16963602
  10. [25]Reeder G. D., Pryor J. B., Wohl M. J. A., Griswell M. L., On attributing negative motives to others who disagree with our opinions. Pers. Soc. Psychol. Bull. 31, 1498– 1510 (2005). 16207769
  11. [27]Pronin E., Gilovich T., Ross L., Objectivity in the eye of the beholder: Divergent perceptions of bias in self versus others. Psychol. Rev. 111, 781– 799 (2004). 15250784
  12. [28]Cohen G. L., Party over policy: The dominating impact of group influence on political beliefs. J. Pers. Soc. Psychol. 85, 808– 822 (2003). 14599246
  13. [29]Kennedy K. A., Pronin E., When disagreement gets ugly: Perceptions of bias and the escalation of conflict. Pers. Soc. Psychol. Bull. 34, 833– 848 (2008). 18469154
  14. [30]Kenworthy J. B., Miller N., Attributional biases about the origins of attitudes: Externality, emotionality, and rationality. J. Pers. Soc. Psychol. 82, 693– 707 (2002). 12003471
  15. [31]Van Boven L., Ehret P. J., Sherman D. K., Psychological barriers to bipartisan public support for climate policy. Perspect. Psychol. Sci. 13, 492– 507 (2018). 29961412
  16. [32]Inglehart R. F., Norris P., Trump, Brexit, and the rise of populism: Economic have-nots and cultural backlash. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2818659. Accessed 14 July 2020.
  17. [34]Mutz D. C., Status threat, not economic hardship, explains the 2016 presidential vote. Proc. Natl. Acad. Sci. U.S.A. 115, E4330– E4339 (2018). 29686081 PMC5948965
  18. [36]Tucker P. D., Torres M., Sinclair B., Smith S. S., Pathways to trump: Republican voters in 2016. Electoral Studies 61, 102035 (2019).
  19. [42]Ross L., Ward A., “ Naive realism in everyday life: Implications for social conflict and misunderstanding” in Values and Knowledge, Brown T., Reed E. S., Turiel E., Eds. (The Jean Piaget Symposium Series, Erlbaum, Hillsdale, NJ, 1996), pp. 103– 135.
  20. [45]Peterson E., Goel S., Iyengar S., Partisan selective exposure in online news consumption: Evidence from the 2016 presidential campaign. Political Sci. Res. Methods, 10.1017/psrm.2019.55 (2019). · DOI
  21. [48]Visser P. S., Krosnick J. A., Development of attitude strength over the life cycle: Surge and decline. J. Pers. Soc. Psychol. 75, 1389– 1410 (1998). 9914661
  22. [49]Berlin I., “ Notes on prejudice” in Liberty: Incorporating Four Essays on Liberty, Hardy H., Ed. (Oxford University Press, Oxford, United Kingdom, 2002), pp. 345– 348.
  23. [50]Schwalbe M. C., Cohen G. L., Ross L. D., The objectivity illusion and voter polarization in the 2016 presidential election. Open Science Framework. https://osf.io/w48f5/. Deposited 21 July 2020. PMC7474588 32817537

Cited by

Sorted by citations

Authors
Schwalbe, M. C., Cohen, G. L., & Ross, L. D.
Affiliations
Stanford University (US)
Corresponding author
  • Schwalbe, Michael C.
  • Ross, Lee D.
Venue
Proceedings of the National Academy of Sciences
Published
2020-08-17
Volume
117
Issue
35
Pages
21218-21229
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W3053985705
Cited by
54
References
5
Citations by year
2026: 4 · 2025: 6 · 2024: 5 · 2023: 24 · 2022: 7 · 2021: 6 · 2020: 2
FWCI
13.04
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • OSF Preprints (OSF Preprints) (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
  • Social Sciences › Sociology and Political Science › Media Influence and Politics
Keywords
voter polarization, 2016 US presidential election, partisanship, presidential debates, perceived bias, closed-mindedness, political attitudes, terrorism stereotypes, political division
MeSH terms
Adult, Attitude, Female, Goals, Humans, Illusions, Longitudinal Studies, Male, Middle Aged, Politics, Social Behavior, Social Perception

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 ›

Are you an author, or do you see a problem with this page? Request a review