La «diversité profonde» selon Charles Taylor : quelle pertinence pour l'Union européenne ?
Bibliographic record
Abstract
Il s’agit, dans cet article, de se demander à quelles conditions la notion taylorienne de «diversité profonde» peut s’appliquer au cas de l’Union européenne (UE). Au travers de ce concept, Charles Taylor met l’accent sur la pluralité antagoniste des modes d’appartenance et d’allégeance au Canada. À un premier niveau d’analyse, plusieurs signes permettent de transposer avec succès un tel diagnostic à l’UE. Toutefois, à un second niveau d’application, des tensions apparaissent entre, d’un côté, les mesures communautariennes défendues par Taylor au nom de la «diversité profonde» et, de l’autre côté, les réquisits d’une vie démocratique «postunanimiste». Au vu de ces tensions, l’article conclut en plaidant pour une dissociation entre identité et légitimité au sein du processus de l’intégration européenne.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".