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Diversity and Expertise in Binary Classification Problems

Year: 2026
Type: article
Abstract: Democratic theorists and social epistemologists often celebrate the epistemic benefits of diversity. One of the cornerstones is the “diversity trumps ability” result by Hong and Page (2004). Ironically, the interplay between diversity and ability is rarely studied in radically different frameworks. In particular, the diversity–expertise trade-off has not been studied systematically for small, deliberative groups facing binary classification problems. To fill this gap, I will introduce a new evidential sources framework and study whether, when, and (if so) why diversity trumps expertise in binary classification problems. The newly gained insights are used to revisit the epistemic credentials of deliberative democracy.
Author: Hein Duijf
Institution: Utrecht University
Language: English
Subfield: Philosophy
Open Access status: hybrid
Estimated APC paid: $3,550
OpenAlex ID: W7131630563
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