Virtue Epistemology and the ‘Epistemic Fitness’ of Democracy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article I explore three distinct advantages of linking virtue epistemology to an epistemic defence of democracy. First, because intellectual agents and communities are the primary focus of epistemic evaluation, virtue epistemology offers political theorists the opportunity to develop an epistemic defence of democracy that takes ‘realism’ seriously (e.g. the cognitive limitations and biases of humans). Second, because virtue epistemology conceives of epistemology as a normative discipline, it builds normative criteria into the exercise of assessing the ‘epistemic fitness’ of a political arrangement (e.g. democracy vs. epistocracy). Third, by assessing the epistemic powers of democracy from a virtue-epistemological perspective, a more robust (Deweyan) conception of democracy needs to be employed and assessed than the minimalist conception employed by the Condorcet Jury Theorem.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it