Significance 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… Click to show full abstract
Significance 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.
               
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