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.
Authors
- Dan M. Kahan, Yale Law School
- Ellen Peters, Ohio State University – Psychology Department; Decision Research; University of Oregon
- Erica Dawson,Cornell University
- Paul Slovic, Decision Research; University of Oregon – Department of Psychology
Paper
Motivated numeracy and enlightened self-government
Posts that link to this paper
- Reflections on the Future of Knowledge Management Societal Knowledge Management
- How Beliefs Shape Reasoning How political views influence the way we interpret data
Posts: Dan Kahan
Quotations: Dan Kahan
Videos: Dan Kahan
Papers: Dan Kahan
Tags: Dan Kahan (9) | motivated reasoning (14)
Blook Search
Google Web Search
Photo Credits: Midjourney (Public Domain)
If you enjoy my work and find it valuable, please consider giving me a little support. Your donation will help cover some of my website hosting expenses.
Make a donation