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Published in: Political Behavior 1/2018

28-02-2017 | Original Paper

Motivated Responding in Studies of Factual Learning

Authors: Kabir Khanna, Gaurav Sood

Published in: Political Behavior | Issue 1/2018

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Abstract

Large partisan gaps in reports of factual beliefs have fueled concerns about citizens’ competence and ability to hold representatives accountable. In three separate studies, we reconsider the evidence for one prominent explanation of these gaps—motivated learning. We extend a recent study on motivated learning that asks respondents to deduce the conclusion supported by numerical data. We offer a random set of respondents a small financial incentive to accurately report what they have learned. We find that a portion of what is taken as motivated learning is instead motivated responding. That is, without incentives, some respondents give incorrect but congenial answers when they have correct but uncongenial information. Relatedly, respondents exhibit little bias in recalling the data. However, incentivizing people to faithfully report uncongenial facts increases bias in their judgments of the credibility of what they have learned. In all, our findings suggest that motivated learning is less common than what the literature suggests, but also that there is a whack-a-mole nature to bias, with reduction in bias in one place being offset by increase in another place.

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Appendix
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Footnotes
1
Partisan gaps in factual beliefs may also arise from selective exposure to information (see, e.g., Stroud 2010, though see also Prior 2013 for a critique of this literature), and motivated assessments of the credibility of information (see, e.g., Lord et al. 1979).
 
2
Nyhan and Reifler test motivated learning using two-sided information flows. They instill false beliefs in respondents via misleading news stories and then attempt to reduce misperceptions with corrective stories. While this design lends external validity to their study, a one-sided context without contradictory information would afford a stricter test of motivated learning.
 
3
Many observational studies suggest motivated learning indirectly, by documenting partisan bias in factual beliefs (Bartels 2002; Shani 2006; Jerit and Barabas 2012), though other observational studies find little bias (e.g., Gaines et al. 2007; Blais et al. 2010).
 
4
It is possible, even likely, that motivated responding also operates outside the survey context, explaining which beliefs people reveal in discussions with social networks, for example. However, in this paper, we focus on motivated responding in surveys.
 
5
We do not incentivize study ratings, because unlike the question about the study’s result, ratings are inherently subjective. The logic of providing incentives to be accurate on subjective questions is unclear. Correspondingly, even if we were to provide incentives, we would not be able to interpret the results unambiguously.
 
6
MTurk is a micro-task market: workers complete small tasks, such as surveys, for money. For details of how samples are recruited on MTurk and general characteristics of the market, see Buhrmester et al. (2011) and Berinsky et al. (2012).
 
7
Attitudes in our study are similar to Americans’ attitudes in two nationally representative surveys. A CBS/New York Times Survey from January 2013 finds that 34% of Americans favor “a federal law requiring a nationwide ban on people other than law enforcement carrying concealed weapons” (including 19% of Republicans a 52% of Democrats). And an Associated Press/GfK Poll from January 2015 finds that 77% favor raising the federal minimum wage (from $7.25/h).
 
8
Kahan et al. (2017) define congeniality on the basis of party identification and ideology. However, overlap between a partisanship - ideology composite and attitudes toward concealed carry is considerably short of 100%. Across the three studies, 47% of self-described liberal Democrats oppose a ban on concealed carry, and 15% of self-described conservative Republicans favor such a ban. We therefore opt for coding congeniality in terms of the attitude most directly related to the data being. Recoding congeniality on the basis of party identification and ideology, following Kahan et al., results in a substantively similar congeniality effect (see “Subsetting Respondents by ‘Ideological Worldview’” in SI).
 
9
We subset high-numeracy respondents in Study 2 to ensure commensurability with Study 1. For concealed carry task results separated out by study, see SI Figs. 5 and 6 in “Covariance Detection Task Results by Study”.
 
10
For equivalent logistic regressions, see SI Tables 7 and 8 in “Concealed Carry Task Results as Logistic Regressions”.
 
11
In Study 2, only 129 respondents (15%) oppose raising the minimum wage. Pooling them with opponents in Study 3 yields a large enough sample to analyze. We obtain substantively similar results we see when analyze each study separately (see SI Figs. 7 and 8 in “Covariance Detection Task Results by Study”).
 
12
One possible explanation for this finding is that behavior in this task was affected by the previous task on concealed carry, since we did not randomize task order. We explore this possibility in “Assessing Spillover” in the SI but find little support for it. Another, related possibility is that respondents mistook the row labels in the second task to be parallel to the row labels in the first task (i.e., cities enacting the given policy are always in the first row). Properly testing this hypothesis (e.g., by fully randomizing row and column labels, and task order) is beyond the scope of this study.
 
13
Pooling concealed carry supporters and opponents, we find that ratings increase from 4.79 if the study is uncongenial to 5.02 if the result supported by the study is congenial (\(t = 1.79\), \(p = .04\)). With incentives, the effect is .42 (\(t=2.30\), \(p=.01\)), and in the absence of incentives, the effect is only .08 (\(t=.46\), \(p=.32\)). All t-tests reported here are one-tailed.
 
14
In the minimum wage task, 23% of respondents are certain of their answer, while only 4% are certain and incorrect. We present these results in more detail in SI Table 11 in “How Confident are Respondents in Their Answers?”.
 
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Metadata
Title
Motivated Responding in Studies of Factual Learning
Authors
Kabir Khanna
Gaurav Sood
Publication date
28-02-2017
Publisher
Springer US
Published in
Political Behavior / Issue 1/2018
Print ISSN: 0190-9320
Electronic ISSN: 1573-6687
DOI
https://doi.org/10.1007/s11109-017-9395-7

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