Motivated reasoning: Election integrity beliefs, outcome acceptance, and polarization before, during, and after the 2020 U.S. Presidential Election.

IF 1.7 3区 心理学 Q3 PSYCHOLOGY, EXPERIMENTAL Motivation and Emotion Pub Date : 2023-01-01 DOI:10.1007/s11031-022-09983-w
Kenneth E Vail, Lindsey Harvell-Bowman, McKenzie Lockett, Tom Pyszczynski, Gabriel Gilmore
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引用次数: 1

Abstract

The 2020 U.S. Presidential Election required voters to not only form opinions of leading candidates, Donald Trump and Joe Biden, but also to make judgments about the integrity of the election itself and what-if anything-to do about it. However, partisan motivated reasoning theory (Leeper and Slothuus, Political Psychology, 35(Suppl 1): 129-156; Lodge and Taber, The rationalizing voter, Cambridge University Press, 2013) suggests judgments are often strongly influenced toward affectively desirable conclusions. Before, during, and after election projections were announced, partisan supporters of Trump and Biden rated: judgments about voter fraud and foreign interference, their acceptance of the results, and their support for recourse against the outcome (e.g., legal challenges, legislative overhauls, violence). Before the election, partisans were mildly concerned about election integrity but willing to accept the outcome without recourse. However, during vote counting, and especially after Biden was projected to be the winner, partisans dramatically changed their judgments in opposite directions, consistent with the affectively desirable conclusions relevant to each group. Biden supporters affirmed the election's integrity and accepted the results whereas Trump supporters disputed the integrity, rejected the results, and began to support recourse against the outcome. Data are consistent with partisan motivated reasoning. Discussion highlights the practical implications.

Supplementary information: The online version contains supplementary material available at 10.1007/s11031-022-09983-w.

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动机推理:2020年美国总统大选之前、期间和之后的选举诚信信念、结果接受和两极分化。
2020年美国总统大选要求选民不仅要形成对主要候选人唐纳德·特朗普和乔·拜登的看法,还要对选举本身的公正性做出判断,以及如果有的话,该怎么做。然而,党派动机推理理论(Leeper and Slothuus, Political Psychology, 35(增刊1):129-156;洛奇和泰伯,理性化选民,剑桥大学出版社,2013)表明,判断往往强烈影响情感上理想的结论。在选举预测公布之前、期间和之后,特朗普和拜登的党派支持者分别对以下方面进行了打分:对选民欺诈和外国干预的判断、他们对结果的接受程度,以及他们对诉诸于结果的支持程度(例如,法律挑战、立法改革、暴力)。在选举之前,党派人士对选举的公正性略有担忧,但愿意接受没有追索权的结果。然而,在计票过程中,特别是在预计拜登将获胜之后,党派人士的判断发生了巨大的变化,朝着相反的方向,与每个群体的情感期望结论相一致。拜登的支持者肯定了选举的公正性,接受了选举结果,而特朗普的支持者则对选举的公正性提出质疑,拒绝了选举结果,开始支持对选举结果提起诉讼。数据与党派动机推理一致。讨论突出了实际意义。补充资料:在线版本提供补充资料,编号:10.1007/s11031-022-09983-w。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
69
期刊介绍: Motivation and Emotion publishes articles on human motivational and emotional phenomena that make theoretical advances by linking empirical findings to underlying processes. Submissions should focus on key problems in motivation and emotion, and, if using non-human participants, should contribute to theories concerning human behavior.  Articles should be explanatory rather than merely descriptive, providing the data necessary to understand the origins of motivation and emotion, to explicate why, how, and under what conditions motivational and emotional states change, and to document that these processes are important to human functioning.A range of methodological approaches are welcome, with methodological rigor as the key criterion.  Manuscripts that rely exclusively on self-report data are appropriate, but published articles tend to be those that rely on objective measures (e.g., behavioral observations, psychophysiological responses, reaction times, brain activity, and performance or achievement indicators) either singly or combination with self-report data.The journal generally does not publish scale development and validation articles.  However, it is open to articles that focus on the post-validation contribution that a new measure can make.  Scale development and validation work therefore may be submitted if it is used as a necessary prerequisite to follow-up studies that demonstrate the importance of the new scale in making a theoretical advance.
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