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Self-Awareness of Political Knowledge

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Abstract

Despite widespread concern over false beliefs about politically-relevant facts, little is known about how strongly Americans believe their answers to poll questions. I propose a conceptual framework for characterizing survey responses about facts: self-awareness, or how well people can assess their own knowledge. I measure self-awareness of political knowledge by eliciting respondent certainty about answers to 24 factual questions about politics. Even on “unfavorable” facts that are inconvenient to the respondent’s political party, more-certain respondents are more likely to answer correctly. Because people are somewhat aware of their ignorance, respondents usually describe their incorrect responses as low-certainty guesses, not high-certainty beliefs. Where misperceptions exist, they tend to be bipartisan: Democrats and Republicans perform poorly on the same questions and explain their answers using similar points of reference.

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Notes

  1. Graham (2018) develops this argument in detail.

  2. The Cambridge English Dictionary defines a belief as “the feeling of being certain that something exists or is true.” Merriam-Webster’s defines a belief as “a state or habit of mind in which trust or confidence is placed in some person or thing.”

  3. On the efficacy of anti-cheating pledges, see Clifford and Jerit (2016).

  4. This is true because calibration captures both the slope and the intercept shift away from the perfect use of the scale. Online Appendix B contrives a degenerate case with high calibration and negative slope.

  5. Online Appendix A presents question-level equivalents of this figure. For simplicity, the figure pools across the partisan cues treatments.

  6. This difference is statistically significant at the 0.05 level pooling across party cue conditions (\(\beta =0.031\), 95% bootstrapped CI = (0.001, 0.061)) but not separately (without cues: \(\beta = 0.031\)\((-\,0.003, -\,0.069)\), with cues: \(\beta = 0.030\)\((-\,0.022, 0.079)\)). Computing the same estimates with robust standard errors yields nearly identical confidence intervals and the same pattern of statistical significance.

  7. Note that because these statistics are computed at the question level, within- and between-person slope both reduce to overall slope, and the high/low statistic is undefined because each respondent names only one certainty level.

  8. On the two stock market questions, 8.4% of respondents used “television”, “watch”, or a variant of “T.V.”, compared with 3.7% of respondents on other questions. In a bivariate OLS regression, this difference of 4.7 percentage points had a robust standard error of 1.2 percentage points.

  9. About 8.5% of party cues respondents used the word “Obama,” “Trump,” or a male pronoun, compared with 4.7% of respondents who did not see party cues. In a bivariate OLS regression, the 3.8 percentage point difference had a robust standard error of 0.7 percentage points.

  10. To test this, I ran the following OLS regression using the subset of data in which Democrats and Republicans answered partisan questions: \(\text {correct}_{ik} \sim \beta _0 + \beta _1 \text {stereotype}_{ik} + \beta _2 \text {favorable}_{ik} + \beta _3 \text {stereotype}_{ik} * \text {favorable}_{ik}\). All variables are indicators. The estimated relationship is almost exactly zero for the unfavorable party (\(\beta _1=0.001\), cluster-robust se \(=0.028\)) and a slightly negative but statistically insignificant relationship for the favorable party (\(\beta _3=-\,0.032\), cluster-robust se \(=0.040\)). Because \(\beta _1\) is near-zero, \(\beta _3\) is a close proxy for the favorable party’s main effect.

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Acknowledgements

This research was funded by the Institution for Social and Policy Studies at Yale University. For helpful comments on earlier versions of this work I thank Alex Coppock, Greg Huber, Kyle Peyton, Sue Stokes, Allison Archer, Nicky Bell, seminar participants at Yale and the Midwest Political Science Association, and three anonymous reviewers. Yale’s Institutional Review Board reviewed and approved the study (2000020387). An overview of the analytic plan was pre-registered in the Evidence in Governance and Politics repository (20170629AA). A replication file is available at dataverse.harvard.edu/dataverse/polbehavior.

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  1. Department of Political Science, Yale University, 115 Prospect St., New Haven, CT, 06511, USA

    Matthew H. Graham

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Correspondence to Matthew H. Graham.

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Graham, M.H. Self-Awareness of Political Knowledge. Polit Behav 42, 305–326 (2020). https://doi.org/10.1007/s11109-018-9499-8

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