Motivated Numeracy and Enlightened Self-Government
Dan M. Kahan
Yale University - Law School
Ohio State University - Psychology Department; Decision Research; University of Oregon
Erica Cantrell Dawson
Decision Research; University of Oregon - Department of Psychology
September 3, 2013
Yale Law School, Public Law Working Paper No. 307
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.
Number of Pages in PDF File: 37
Date posted: September 8, 2013
© 2016 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollobot1 in 0.266 seconds