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The Affective Tipping Point: Do Motivated Reasoners Ever “Get It”?
Abstract
In order to update candidate evaluations voters must acquire information and determine whether that new information supports or opposes their candidate expectations. Normatively, new negative information about a preferred candidate should result in a downward adjustment of an existing evaluation. However, recent studies show exactly the opposite; voters become more supportive of a preferred candidate in the face of negatively valenced information. Motivated reasoning is advanced as the explanation, arguing that people are psychologically motivated to maintain and support existing evaluations. Yet it seems unlikely that voters do this ad infinitum. To do so would suggest continued motivated reasoning even in the face of extensive disconfirming information. In this study we consider whether motivated reasoning processes can be overcome simply by continuing to encounter information incongruent with expectations. If so, voters must reach a tipping point after which they begin more accurately updating their evaluations. We show experimental evidence that such an affective tipping point does in fact exist. We also show that as this tipping point is reached, anxiety increases, suggesting that the mechanism that generates the tipping point and leads to more accurate updating may be related to the theory of affective intelligence. The existence of a tipping point suggests that voters are not immune to disconfirming information after all, even when initially acting as motivated reasoners.
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Citations
Cites
Development and validation of brief measures of positive and negative affect: The PANAS scales.
Watson, D., Clark, L. A., & Tellegen, A. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.6.1063 · Cited by 32,433
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
The case for motivated reasoning.
Kunda, Z. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.108.3.480 · Cited by 9,022
Lord, C. G., Ross, L., & Lepper, M. R. (1979) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.37.11.2098 · Cited by 4,583
Crawford, J. R., & Henry, J. D. (2004) · British Journal of Clinical Psychology · doi:10.1348/0144665031752934 · Cited by 2,957 · cited 2×
“Previous studies have shown the NA scale itself to be a good measure of anxious states (Crawford and Henry, 2004; Mehrabian, 1997) and it is widely used in social psychology.”
BackgroundLodge, M., & Taber, C. S. (2005) · Political Psychology · doi:10.1111/j.1467-9221.2005.00426.x · Cited by 588
Cited by
When Corrections Fail: The Persistence of Political Misperceptions
Nyhan, B., & Reifler, J. (2010) · Political Behavior · doi:10.1007/s11109-010-9112-2 · Cited by 3,173
Pennycook, G., & Rand, D. G. (2019) · Cognition · doi:10.1016/j.cognition.2018.06.011 · Cited by 2,022
The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics
Flynn, D. J., Nyhan, B., & Reifler, J. (2017) · Political Psychology · doi:10.1111/pops.12394 · Cited by 1,183
Media and Political Polarization
Prior, M. (2013) · Annual Review of Political Science · doi:10.1146/annurev-polisci-100711-135242 · Cited by 1,125
Political Parties, Motivated Reasoning, and Public Opinion Formation
Leeper, T. J., & Slothuus, R. (2014) · Political Psychology · doi:10.1111/pops.12164 · Cited by 722
Weeks, B. E. (2015) · Journal of Communication · doi:10.1111/jcom.12164 · Cited by 531
Segregation by Design: Local Politics and Inequality in American Cities
Trounstine, J. (2018) · doi:10.1017/9781108555722 · Cited by 428
Social Media, Echo Chambers, and Political Polarization
Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373
Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments
Guess, A., & Coppock, A. (2020) · British Journal of Political Science · doi:10.1017/s0007123418000327 · Cited by 372
Bisgaard, M. (2015) · The Journal of Politics · doi:10.1086/681591 · Cited by 347
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284
Why People “Don’t Trust the Evidence”: Motivated Reasoning and Scientific Beliefs
Kraft, P. W., Lodge, M., & Taber, C. S. (2015) · The ANNALS of the American Academy of Political and Social Science · doi:10.1177/0002716214554758 · Cited by 283
The gateway belief model: a large-scale replication
van der Linden, S., Leiserowitz, A., & Maibach, E. (2019) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2019.01.009 · Cited by 262
Jerit, J., & Zhao, Y. (2020) · Annual Review of Political Science · doi:10.1146/annurev-polisci-050718-032814 · Cited by 263
Do (microtargeted) deepfakes have real effects on political attitudes?
Dobber, T., Metoui, N., Trilling, D., Helberger, N., & de Vreese, C. (2021) · The International Journal of Press/Politics · doi:10.1177/1940161220944364 · Cited by 256
Parkhurst, J. (2016) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · doi:10.4324/9781315675008 · Cited by 756
The role of evidence in politics: Motivated reasoning and persuasion among politicians.
Baekgaard, M., Christensen, J., Dahlmann, C. M., Mathiasen, A., & Petersen, N. B. G. (2019) · British Journal of Political Science · doi:10.1017/s0007123417000084 · Cited by 209
Weeks, B. E., & Garrett, R. K. (2014) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edu005 · Cited by 191
Emotional Responses to the Charlie Hebdo Attacks: Addressing the Authoritarianism Puzzle
Vasilopoulos, P., Marcus, G. E., & Foucault, M. (2018) · Political Psychology · doi:10.1111/pops.12439 · Cited by 137
Conformity in Groups: The Effects of Others’ Views on Expressed Attitudes and Attitude Change
Levitan, L. C., & Verhulst, B. (2016) · Political Behavior · doi:10.1007/s11109-015-9312-x · Cited by 129
The Uncertainty Paradox: Perceived Threat Moderates the Effect of Uncertainty on Political Tolerance
Haas, I. J., & Cunningham, W. A. (2014) · Political Psychology · doi:10.1111/pops.12035 · Cited by 96
Opinion Dynamics with Confirmation Bias
Allahverdyan, A. E., & Galstyan, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099557 · Cited by 90
What Motivates Reasoning? A Theory of Goal‐Dependent Political Evaluation
Groenendyk, E., & Krupnikov, Y. (2021) · American Journal of Political Science · doi:10.1111/ajps.12562 · Cited by 85
Elections and Satisfaction with Democracy: Citizens, Processes and Outcomes
Daoust, J.-F., & Nadeau, R. (2023) · doi:10.1017/9781009128032 · Cited by 28
The Somatic Marker Hypothesis and Political Life
Verweij, M., & Damasio, A. (2019) · Oxford Research Encyclopedia of Politics · doi:10.1093/acrefore/9780190228637.013.928 · Cited by 15
Metadata
- Authors
- Redlawsk, D. P., Civettini, A. J. W., & Emmerson, K. M.
- Venue
- Political Psychology
- Publisher
- Wiley
- Published
- 2010-07-12
- Volume
- 31
- Issue
- 4
- Pages
- 563-593
- ISSN
- 0162-895X (ISSN-L)
- 1467-9221
- OpenAlex
- W1519575580
- Cited by
- 571
- References
- 6
- FWCI
- 100.82
- Type
- journal article
- Language
- en
- Open access
- closed
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