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Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Voter Competence and Epistemic Arguments for Democracy

Authors: Balayan, Arshak;

Voter Competence and Epistemic Arguments for Democracy

Abstract

Epistemic democrats argue that democracy is better than other political regimes not only morally, but also epistemically. They claim that, despite well-documented public ignorance, democratic decision-making is epistemically preferable to alternatives: as decision-making mechanisms democratic deliberation and majority vote through free and fair elections outperform decisions by expert bodies. There are several theoretical explanations for why this might be the case. This paper discusses the applicability of Condorcet’s Jury Theorem (CJT) and the Diversity Trumps Ability Theorem (DTAT) proved by Lu Hong and Scott E. Page. These two theorems are believed to explain how bigger groups of moderately competent problem solvers outperform smaller groups of individually more competent problem solvers. The analysis of these theorems leads to the conclusion that more inclusive democratic deliberation as well as free fair and periodic democratic elections will hardly satisfy democratic needs or outperform expert bodies. To function epistemically well democracies need to heavily rely on experts. The paper concludes with the conjecture that heavy institutionalization of expertise might be the best way to develop democracies.

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Keywords

Condorcet's jury theorem, Epistemic democrats, experts, Knowledge problem, Democracy, diversity trumps ability theorem

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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