Représentation de groupe et démocratie délibérative : une alliance malaisée1
Bibliographic record
Abstract
Cet article examine la place du concept d’impartialité dans les théories délibératives de la démocratie. C’est à partir de certaines critiques féministes que sont discutés deux défis lancés à la théorie délibérative et qui sont étroitement liés : le premier porte essentiellement sur le critère du raisonnable et l’idée d’offre de raisons ; le second concerne les circonstances sociales et politiques contingentes dans lesquelles les perspectives des groupes marginalisés peuvent influencer le jugement des autres citoyens. Certains des changements qui devraient être apportés à la théorie délibérative afin qu’elle puisse tenir compte de ces préoccupations sont ensuite proposés. Finalement, les implications de tels changements pour nos notions plus générales de vertu et de responsabilité de la citoyenneté sont examinées.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".