While a dominant narrative of American life paints a bleak picture of poorly informed internet partisans duking it out over a landscape denuded of anything resembling truth or reality, a new study from the Georgia Tech School of Public Policy offers a different take while also advancing the use of machine learning in the social sciences and an understanding of the importance of open-access, science-based information to everyday Americans.
The study, published Feb. 23, 2022, in the prestigious Proceedings of the National Academy of Sciences (PNAS), analyzed the reasons for 1.6 million downloads of National Academies of Sciences, Engineering, and Medicine (NASEM) consensus reports, considered among the highest credibility science-based literature.
The resulting analysis, which included U.S. downloads only, is the first to look at who is using such information and why. Professor Diana Hicks, Assistant Professor Omar I. Asensio, and Ph.D. students Matteo Zullo and Ameet Doshi, all of Georgia Tech’s School of Public Policy, co-authored the study.
They found that while nearly half of the reports were downloaded for academic purposes, even more were accessed by people outside strictly educational settings, such as veterans, chaplains, and writers. The word “edification” appeared 3,700 times in the data set, signaling a strong desire for lifelong learning among users.
“This study shows strong demand among everyday Americans for the highest quality information to help improve the job they are doing, to help their relatives, neighbors, and communities, and in some cases simply to learn for learning’s sake,” said Hicks. “We never hear these stories because everyone is focusing on all the misinformation that goes out over social media.”
In seeking to understand how to protect the public information sphere from corruption, researchers understandably focus on dysfunction. However, parts of the public information ecosystem function very well, and understanding this as well will help in protecting and developing existing strengths. Here, we address this gap, focusing on public engagement with high-quality science-based information, consensus reports of the National Academies of Science, Engineering, and Medicine (NASEM). Attending to public use is important to justify public investment in producing and making freely available high-quality, scientifically based reports. We deploy Bidirectional Encoder Representations from Transformers (BERT), a high-performing, supervised machine learning model, to classify 1.6 million comments left by US downloaders of National Academies reports responding to a prompt asking how they intended to use the report. The results provide detailed, nationwide evidence of how the public uses open access scientifically based information. We find half of reported use to be academic—research, teaching, or studying. The other half reveals adults across the country seeking the highest-quality information to improve how they do their job, to help family members, to satisfy their curiosity, and to learn. Our results establish the existence of demand for high-quality information by the public and that such knowledge is widely deployed to improve provision of services. Knowing the importance of such information, policy makers can be encouraged to protect it.
How were NASEM reports used? Classification into 64 categories of 1.6 million comments left by US downloaders of NASEM reports between 2011 and 2020. Downloaders were asked how they will use the report. BERT machine learning algorithm was used to classify. Source: 10.1073/pnas.2107760119
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area.
He earned his MLIS degree from Wayne State University in Detroit.
Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.
