Widespread use of National Academies consensus reports by the American public

Diana Hicks, Matteo Zullo, Ameet Doshi and Omar I. Asensio
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Diana Hicks: a School of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332;
Matteo Zullo: a School of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332;; b Andrew Young School of Policy Studies, Georgia State University, Atlanta, GA 30303;
Ameet Doshi: a School of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332;; c Princeton University Library, Princeton University, Princeton, NJ 08544;
Omar I. Asensio: a School of Public Policy, Georgia Institute of Technology, Atlanta, GA 30332;; d Institute for Data Engineering & Science, Georgia Institute of Technology, Atlanta, GA 30308

Proceedings of the National Academy of Sciences, 2022, vol. 119, issue 9, e2107760119

Abstract: Advocates for open access argue that people need scientific information, although they lack evidence for this. Using Google’s recently developed deep learning natural language processing model, which offers unrivalled comprehension of subtle differences in meaning, 1.6 million people downloading National Academies reports were classified, not just into broad categories such as researchers and teachers but also precisely delineated small groups such as hospital chaplains, veterans, and science fiction authors. The results reveal adults motivated to seek out the most credible sources, engage with challenging material, use it to improve the services they provide, and learn more about the world they live in. The picture contrasts starkly with the dominant narrative of a misinformed and manipulated public targeted by social media.

Keywords: BERT; natural language processing; public understanding of science; machine learning (search for similar items in EconPapers)
Date: 2022
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