Information Deprivation and Democratic Engagement

Philosophy of Science 90 (5) (2023)
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Abstract

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites' conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality and that doing so may improve the predictive and explanatory power of extant models.

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Adrian K. Yee
Lingnan University

Citations of this work

Machine Learning, Misinformation, and Citizen Science.Adrian K. Yee - 2023 - European Journal for Philosophy of Science 13 (56):1-24.

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References found in this work

Science, Policy, and the Value-Free Ideal.Heather Douglas - 2009 - University of Pittsburgh Press.
Objectivity.Lorraine Daston & Peter Galison - 2007 - Cambridge, Mass.: Zone Books. Edited by Peter Galison.
What is Disinformation?Don Fallis - 2015 - Library Trends 63 (3):401-426.
Misinformation as Immigration Control.Mollie Gerver - 2017 - Res Publica 23 (4):495-511.

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