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Correcting Bias in Perceptions of Public Opinion Among American Elected Officials: Results from Two Field Experiments

Published online by Cambridge University Press:  03 March 2020

Joshua L. Kalla Open the ORCID record for Joshua L. Kalla [Opens in a new window]  and
Ethan Porter
Joshua L. Kalla*
Affiliation:
Department of Political Science and Department of Statistics and Data Science, Yale University, USA
Ethan Porter
Affiliation:
School of Media and Public Affairs, George Washington University, USA
*
*Corresponding author. E-mail: [email protected]
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Abstract

While concerns about the public's receptivity to factual information are widespread, much less attention has been paid to the factual receptivity, or lack thereof, of elected officials. Recent survey research has made clear that US legislators and legislative staff systematically misperceive their constituents' opinions on salient public policies. This study reports the results from two field experiments designed to correct misperceptions of sitting US legislators. The legislators (n = 2,346) were invited to access a dashboard of constituent opinion generated using the 2016 Cooperative Congressional Election Study. Despite extensive outreach efforts, only 11 per cent accessed the information in Study 1 and only 2.3 per cent did so in Study 2. More troubling for democratic norms, legislators who accessed constituent opinion data were no more accurate at perceiving their constituents' opinions. The findings underscore the challenges confronting efforts to improve the accuracy of elected officials' perceptions and suggest that elected officials may indeed resist factual information.

Keywords

misperceptionselected officialsfield experiments
Type
Letter
Information
British Journal of Political Science , Volume 51 , Issue 4 , October 2021 , pp. 1792 - 1800
Copyright
Copyright © Cambridge University Press 2020

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References

Ansolabehere, S and Schaffner, B (2017) CCES Common Content, 2016. Available from http://dx.doi.org/10.7910/DVN/GDF6Z0.CrossRefGoogle Scholar
Barber, MJ (2016) Representing the preferences of donors, partisans, and voters in the US Senate. Public Opinion Quarterly 80(S1), 225–249.CrossRefGoogle Scholar
Bawn, K et al. (2012) A theory of political parties: groups, policy demands and nominations in American politics. Perspectives on Politics 10(3), 571–597.CrossRefGoogle Scholar
Berinsky, A (2017) Rumors and health care reform: experiments in political misinformation. British Journal of Political Science 47(2), 241–262.CrossRefGoogle Scholar
Broockman, D, Kalla, J and Sekhon, JS (2017) The design of field experiments with survey outcomes: a framework for selecting more efficient, robust, and ethical designs. Political Analysis 25(4), 435–464.CrossRefGoogle Scholar
Broockman, D et al. (2019) Why local party leaders don't support nominating centrists. British Journal of Political Science. Doi: 10.1017/S0007123419000309.Google Scholar
Broockman, DE and Skovron, C (2018) Bias in perceptions of public opinion among political elites. American Political Science Review 112(3), 542–563.CrossRefGoogle Scholar
Burke, E (1986) Speech to the Electors of Bristol. Available from http://press-pubs.uchicago.edu/founders/documents/v1ch13s7.html.Google Scholar
Butler, D and Nickerson, D (2011) Can learning constituency opinion affect how legislators vote? Results from a field experiment. Quarterly Journal of Political Science 6(1), 55–83.CrossRefGoogle Scholar
Butler, DM and Dynes, AM (2016) How politicians discount the opinions of constituents with whom they disagree. American Journal of Political Science 60(4), 975–989.CrossRefGoogle Scholar
Gelman, A and Little, T (1997) Poststratification into many categories using hierarchical logistic regression. Survey Methodology 23(2), 127–135.Google Scholar
Gilens, M (2012) Affluence and Influence: Economic Inequality and Political Power in America. Princeton, NJ: University Press.Google Scholar
Green, D, Wilke, A and Cooper, J (2017) Reducing Intimate Partner Violence through Informal Social Control: A Mass Media Experiment in rural Uganda. Technical report. New York: Columbia University.Google Scholar
Grinberg, N et al. (2019) Fake news on Twitter during the 2016 US presidential election. Science 363(6425), 374–378.CrossRefGoogle Scholar
Guess, A and Coppock, A (2018) Does counter-attitudinal information cause backlash? Results from three large survey experiments. British Journal of Political Science. Doi: 10.1017/S0007123418000327.Google Scholar
Guess, A, Nagler, J and Tucker, J (2019) Less than you think: prevalence and predictors of fake news dissemination on Facebook. Science Advances 5(1), 1–8.CrossRefGoogle ScholarPubMed
Hacker, JS and Pierson, P (2010) Winner-take-all Politics: How Washington Made the Rich Richer–and Turned its Back on the Middle Class. New York: Simon and Schuster.Google Scholar
Hertel-Fernandez, A, Mildenberger, M and Stokes, LC (2019) Legislative staff and representation in congress. American Political Science Review 113(1), 1–18.CrossRefGoogle Scholar
Hill, SJ (2017) Learning together slowly: Bayesian learning about political facts. The Journal of Politics 79(4), 1403–1418.CrossRefGoogle Scholar
Hopkins, D (2018) The Increasingly United States: How and Why American Political Behavior Nationalized. Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
Iyengar, S and Massey, DS (2019) Scientific communication in a post-truth society. Proceedings of the National Academy of Sciences 116(16), 7656–7661.CrossRefGoogle Scholar
Kalla, JL and Broockman, DE (2016) Campaign contributions facilitate access to congressional officials: a randomized field experiment. American Journal of Political Science 60(3), 545–558.CrossRefGoogle Scholar
Kalla, J and Porter, E (2020) Replication Data for: Correcting Bias in Perceptions of Public Opinion Among American Elected Officials: Results from Two Field Experiments, https://doi.org/10.7910/DVN/0A1AM3, Harvard Dataverse, V1, UNF:6:W8vf8R+Y0WH9O1IAqv5x1g== [fileUNF]Google Scholar
Kraus, MW, Rucker, JM and Richeson, JA (2017) Americans misperceive racial economic equality. Proceedings of the National Academy of Sciences 114(39), 10324–10331.CrossRefGoogle ScholarPubMed
Lax, J and Phillips, J (2009) How should we estimate public opinion in the states? American Journal of Political Science 53(1), 107–121.CrossRefGoogle Scholar
Lazer, DMJ et al. (2018) The science of fake news. Science 359(6380), 1094–1096.CrossRefGoogle ScholarPubMed
Lee, N et al. (2019) More Accurate Yet More Polarized? Comparing the Factual Beliefs of Government Officials and the Public. Working paper. Palo Alto, CA: Stanford University.Google Scholar
Leighley, JE and Oser, J (2018) Representation in an era of political and economic inequality: how and when citizen engagement matters. Perspectives on Politics 16(2), 328–344.CrossRefGoogle Scholar
Mansbridge, J (2003) Rethinking representation. American Political Science Review 97(4), 515–528.CrossRefGoogle Scholar
Mayhew, DR (1974) Congress: The Electoral Connection. New Haven, CT: Yale University Press.Google Scholar
Miler, K (2010) Constituency Representation in Congress: The View From Capitol Hill. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Montgomery, JM, Nyhan, B and Torres, M (2018) How conditioning on posttreatment variables can ruin your experiment and what to do about it. American Journal of Political Science 62(3), 760–775.CrossRefGoogle Scholar
Nickerson, D (2005) Scalable protocols offer efficient design for field experiments. Political Analysis 13(3), 233–252.CrossRefGoogle Scholar
Nyhan, B and Reifler, J (2014) The effect of fact-checking on elites: a field experiment on US state legislators. American Journal of Political Science 59(3), 628–640.CrossRefGoogle Scholar
Park, D et al. (2004) Bayesian multilevel estimation with poststratification: state-level estimates from national polls. Political Analysis 12(4), 375–385.CrossRefGoogle Scholar
Pennycook, G and Rand, DG (2019) Fighting misinformation on social media using crowdsourced judgments of news source quality. Proceedings of the National Academy of Sciences 116(7), 2521–2526.CrossRefGoogle ScholarPubMed
Pitkin, HF (1967) The Concept of Representation. Berkeley: University of California Press.CrossRefGoogle Scholar
Porter, E and Wood, TJ (2019) False Alarm: The Truth About Political Mistruths in the Trump Era. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Shor, B and McCarty, N (2011) The ideological mapping of American legislatures. American Political Science Review 105(3), 530–551.CrossRefGoogle Scholar
Teele, DL, Kalla, J and Rosenbluth, F (2018) The ties that double bind: social roles and women's underrepresentation in politics. American Political Science Review 112(3), 525–541.CrossRefGoogle Scholar
Warshaw, C and Rodden, J (2012) How should we measure district-level public opinion on individual issues? The Journal of Politics 74(1), 203–219.CrossRefGoogle Scholar
Wood, T and Porter, E (2019) The elusive backfire effect: mass attitudes’ steadfast factual adherence. Political Behavior 41(1), 135–163.CrossRefGoogle Scholar
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