Beyond the Running Tally: Partisan Bias in Political Perceptions

By Larry M. Bartels. 2002

1,460 citations recorded by the source corpus.

Subfields: Political Science and International Relations, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e697fb32bc14ca21d6adbd1f4bfdb89279224515

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Citations in the corpus

Political Parties, Motivated Reasoning, and Public Opinion Formation (2014, background): “…that partisans show dramatic differences in their perceptions and interpretations of key political events such as economic changes and war (Bartels, 2002; Gaines, Kuklinski, Quirk, Peyton, & Verkuilen, 2007; Lavine et al., 2012), prior attitudes color the evaluations of arguments…”
Let's Put Garbage-Can Regressions and Garbage-Can Probits Where They Belong (2005, background): “Knowing how Bayesian theory works, for example, allowed Bartels (2002) to discover errors in the seemingly persuasive informal logic with which public opinion researchers have treated opinion change.”
The roles of information deficits and identity threat in the prevalence of misperceptions (2019, methodology): “We expected to see widespread divergence in beliefs about changes in the number of jobs under Obama because the state of the economy is a factual issue that lends itself to biased processing (Bartels 2002).”
Partisanship and Economic Behavior: Do Partisan Differences in Economic Forecasts Predict Real Economic Behavior? (2009, background): “Similarly, only about 20% of strong Democrats said inflation was better versus 70% of strong Republicans (Bartels 2002, Figure 3).”
Belief Echoes: The Persistent Effects of Corrected Misinformation (2016, background): “Information affects attitudes, but attitudes also affect what facts people choose to accept or reject (Bartels, 2002; Lodge, Taber, & Weber, 2006).”
Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments (2018, background): “For example, whether ‘unbiased’ Bayesian learning implies convergence or parallel updating in evaluations of political figures has been the subject of continuing debate (Bartels 2002; Bullock 2009; Gerber and Green 1999). Bayesian rationality has often been taken to rule out polarization, but even t”
Vote Switching in the 2016 Election: How Racial and Immigration Attitudes, Not Economics, Explain Shifts in White Voting (2019, background): “…of finances are influenced by a respondent’s partisanship and the party that happens to be in power (Healy, Persson, and Snowberg 2017), though far less so than evaluations of the national economy (Bartels 2002), suggesting that part of the effect found here could be simply reflecting partisanship.”
The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics (2017, background): “By the deﬁnition provided above, misperceptions appear to be widespread (e.g., Ramsay, Kull, Lewis, and Subias, 2010) on issues ranging from the economy (e.g., Bartels, 2002) to foreign policy (e.g., Kull, Ramsay, & Lewis, 2003).”
Political Attitudes and the Processing of Misinformation Corrections (2018, background): “…with one’s attitudes and beliefs, while being distrustful of evidence that runs counter to one’s attitudes and beliefs (i.e., motivated reasoning, cf. Bartels, 2002; Edwards & Smith, 1996; W. Hart et al., 2009; Kruglanski & Webster, 1996; Kunda, 1990; Lord, Ross, & Lepper, 1979; Redlawsk, 2002;…”
Rumors and Health Care Reform: Experiments in Political Misinformation (2015, neutral): “26 Bartels 2002.”