Information Deprivation and Democratic Engagement.

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 ep...

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Publicado en:Philosophy of Science Vol. 90; no. 5; pp. 1110 - 1120
Autor principal: Yee, Adrian K.
Formato: Artículo
Publicado: Cambridge University Press Dec2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Information Deprivation and Democratic Engagement.
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        au: Yee, Adrian K.
        affil:
          Institute for the History & Philosophy of Science and Technology (IHPST), University of Toronto, Canada
          Department of Philosophy, Lingnan University, Hong Kong Catastrophic Risk Centre, Hong Kong
      su:
        Statistical learning
        Statistics
        Social scientists
        Machine learning
        Operational definitions
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        subj:
          Statistical learning
          Statistics
          Social scientists
          Machine learning
          Operational definitions
      ab: 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 doing so may improve the predictive and explanatory power of extant models.
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    language: English
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