Motivated numeracy and enlightened self-government
01 May 2017-Vol. 1, Iss: 1, pp 54-86
TL;DR: This article conducted an experiment to probe two alternative answers: the science comprehension thesis (SCT), which identifies defects in the public's knowledge and reasoning capacities as the source of such controversies; and the identity-protective cognition thesis (ICT), which treats cultural conflict as disabling the faculties that members of the public use to make sense of decision-relevant science.
Abstract: Why does public conflict over societal risks persist in the face of compelling and widely accessible scientific evidence? We conducted an experiment to probe two alternative answers: the ‘science comprehension thesis’ (SCT), which identifies defects in the public's knowledge and reasoning capacities as the source of such controversies; and the ‘identity-protective cognition thesis’ (ICT), which treats cultural conflict as disabling the faculties that members of the public use to make sense of decision-relevant science. In our experiment, we presented subjects with a difficult problem that turned on their ability to draw valid causal inferences from empirical data. As expected, subjects highest in numeracy – a measure of the ability and disposition to make use of quantitative information – did substantially better than less numerate ones when the data were presented as results from a study of a new skin rash treatment. Also as expected, subjects’ responses became politically polarized – and even less accurate – when the same data were presented as results from the study of a gun control ban. But contrary to the prediction of SCT, such polarization did not abate among subjects highest in numeracy; instead, it increased. This outcome supported ICT, which predicted that more numerate subjects would use their quantitative-reasoning capacity selectively to conform their interpretation of the data to the result most consistent with their political outlooks. We discuss the theoretical and practical significance of these findings.
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TL;DR: The results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.
Abstract: Across two studies with more than 1,700 U.S. adults recruited online, we present evidence that people share false claims about COVID-19 partly because they simply fail to think sufficiently about whether or not the content is accurate when deciding what to share. In Study 1, participants were far worse at discerning between true and false content when deciding what they would share on social media relative to when they were asked directly about accuracy. Furthermore, greater cognitive reflection and science knowledge were associated with stronger discernment. In Study 2, we found that a simple accuracy reminder at the beginning of the study (i.e., judging the accuracy of a non-COVID-19-related headline) nearly tripled the level of truth discernment in participants' subsequent sharing intentions. Our results, which mirror those found previously for political fake news, suggest that nudging people to think about accuracy is a simple way to improve choices about what to share on social media.
914 citations
TL;DR: This article found that cognitive reflection test performance is negatively correlated with perceived accuracy of fake news, and positively correlated with the ability to distinguish fake news from real news, even for headlines that align with individuals' political ideology.
707 citations
TL;DR: In this article, the authors provide a perspective into the main ideas and findings emerging from the growing literature on motivated beliefs and reasoning, emphasizing that beliefs often fulfill important psychological and functional needs of the individual.
Abstract: In the economic models of old, agents had backward-looking expectations, arising from simple extrapolation or error-correction rules. Then came the rational-expectations revolution in macroeconomics, and in microeconomics the spread and increasing refinements of modern game theory. Agents were now highly sophisticated information processors, who could not be systematically fooled. This approach reigned for several decades until the pendulum swung back with the rise of behavioral economics and its emphasis on “heuristics and biases” (as in Tversky and Kahneman 1974). Overconfidence, confirmation bias, distorted probability weights, and a host of other “wired-in” cognitive mistakes are now common assumptions in many areas of economics. Over the last decade or so, the pendulum has started to swing again toward some form of adaptiveness, or at least implicit purposefulness, in human cognition. In this paper, we provide a perspective into the main ideas and findings emerging from the growing literature on motivated beliefs and reasoning. This perspective emphasizes that beliefs often fulfill important psychological and functional needs of the individual. Economically relevant examples include confidence in ones’ abilities, moral self-esteem, hope and anxiety reduction, social identity, political ideology and religious faith. People thus hold certain beliefs in part because
371 citations
TL;DR: This article reviews the available evidence and finds support for four claims: (1) Academic psychology once had considerable political diversity, but has lost nearly all of it in the last 50 years, and increased political diversity would improve social psychological science by reducing the impact of bias mechanisms such as confirmation bias, and by empowering dissenting minorities to improve the quality of the majority's thinking.
Abstract: Psychologists have demonstrated the value of diversity--particularly diversity of viewpoints--for enhancing creativity, discovery, and problem solving. But one key type of viewpoint diversity is lacking in academic psychology in general and social psychology in particular: political diversity. This article reviews the available evidence and finds support for four claims: (1) Academic psychology once had considerable political diversity, but has lost nearly all of it in the last 50 years. (2) This lack of political diversity can undermine the validity of social psychological science via mechanisms such as the embedding of liberal values into research questions and methods, steering researchers away from important but politically unpalatable research topics, and producing conclusions that mischaracterize liberals and conservatives alike. (3) Increased political diversity would improve social psychological science by reducing the impact of bias mechanisms such as confirmation bias, and by empowering dissenting minorities to improve the quality of the majority's thinking. (4) The underrepresentation of non-liberals in social psychology is most likely due to a combination of self-selection, hostile climate, and discrimination. We close with recommendations for increasing political diversity in social psychology.
338 citations
TL;DR: The authors found no corrections capable of triggering backfire, despite testing precisely the kinds of polarized issues where backfire should be expected Evidence of factual backfire is far more tenuous than prior research suggests by and large, citizens heed factual information, even when such information challenges their ideological commitments.
Abstract: Can citizens heed factual information, even when such information challenges their partisan and ideological attachments? The “backfire effect,” described by Nyhan and Reifler (Polit Behav 32(2):303–330 https://doiorg/101007/s11109-010-9112-2
, 2010), says no: rather than simply ignoring factual information, presenting respondents with facts can compound their ignorance In their study, conservatives presented with factual information about the absence of Weapons of Mass Destruction in Iraq became more convinced that such weapons had been found The present paper presents results from five experiments in which we enrolled more than 10,100 subjects and tested 52 issues of potential backfire Across all experiments, we found no corrections capable of triggering backfire, despite testing precisely the kinds of polarized issues where backfire should be expected Evidence of factual backfire is far more tenuous than prior research suggests By and large, citizens heed factual information, even when such information challenges their ideological commitments
336 citations
References
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01 Jan 1987
TL;DR: In this article, a survey of drinking behavior among men of retirement age was conducted and the results showed that the majority of the participants reported that they did not receive any benefits from the Social Security Administration.
Abstract: Tables and Figures. Glossary. 1. Introduction. 1.1 Overview. 1.2 Examples of Surveys with Nonresponse. 1.3 Properly Handling Nonresponse. 1.4 Single Imputation. 1.5 Multiple Imputation. 1.6 Numerical Example Using Multiple Imputation. 1.7 Guidance for the Reader. 2. Statistical Background. 2.1 Introduction. 2.2 Variables in the Finite Population. 2.3 Probability Distributions and Related Calculations. 2.4 Probability Specifications for Indicator Variables. 2.5 Probability Specifications for (X,Y). 2.6 Bayesian Inference for a Population Quality. 2.7 Interval Estimation. 2.8 Bayesian Procedures for Constructing Interval Estimates, Including Significance Levels and Point Estimates. 2.9 Evaluating the Performance of Procedures. 2.10 Similarity of Bayesian and Randomization--Based Inferences in Many Practical Cases. 3. Underlying Bayesian Theory. 3.1 Introduction and Summary of Repeated--Imputation Inferences. 3.2 Key Results for Analysis When the Multiple Imputations are Repeated Draws from the Posterior Distribution of the Missing Values. 3.3 Inference for Scalar Estimands from a Modest Number of Repeated Completed--Data Means and Variances. 3.4 Significance Levels for Multicomponent Estimands from a Modest Number of Repeated Completed--Data Means and Variance--Covariance Matrices. 3.5 Significance Levels from Repeated Completed--Data Significance Levels. 3.6 Relating the Completed--Data and Completed--Data Posterior Distributions When the Sampling Mechanism is Ignorable. 4. Randomization--Based Evaluations. 4.1 Introduction. 4.2 General Conditions for the Randomization--Validity of Infinite--m Repeated--Imputation Inferences. 4.3Examples of Proper and Improper Imputation Methods in a Simple Case with Ignorable Nonresponse. 4.4 Further Discussion of Proper Imputation Methods. 4.5 The Asymptotic Distibution of (Qm,Um,Bm) for Proper Imputation Methods. 4.6 Evaluations of Finite--m Inferences with Scalar Estimands. 4.7 Evaluation of Significance Levels from the Moment--Based Statistics Dm and Dm with Multicomponent Estimands. 4.8 Evaluation of Significance Levels Based on Repeated Significance Levels. 5. Procedures with Ignorable Nonresponse. 5.1 Introduction. 5.2 Creating Imputed Values under an Explicit Model. 5.3 Some Explicit Imputation Models with Univariate YI and Covariates. 5.4 Monotone Patterns of Missingness in Multivariate YI. 5.5 Missing Social Security Benefits in the Current Population Survey. 5.6 Beyond Monotone Missingness. 6. Procedures with Nonignorable Nonresponse. 6.1 Introduction. 6.2 Nonignorable Nonresponse with Univariate YI and No XI. 6.3 Formal Tasks with Nonignorable Nonresponse. 6.4 Illustrating Mixture Modeling Using Educational Testing Service Data. 6.5 Illustrating Selection Modeling Using CPS Data. 6.6 Extensions to Surveys with Follow--Ups. 6.7 Follow--Up Response in a Survey of Drinking Behavior Among Men of Retirement Age. References. Author Index. Subject Index. Appendix I. Report Written for the Social Security Administration in 1977. Appendix II. Report Written for the Census Bureau in 1983.
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