Comprendre l’hétérogénéité sociale pour faire valoir la diversité1
Bibliographic record
Abstract
Alors que le vocable « diversité » gagne en popularité et que l’on dénonce avec lui la « norme mythique » d’un sujet social universel, on observe une confusion et un glissement sémantique entre les termes « diversité » et « hétérogénéité sociale intragroupe ». Les auteures proposent une comparaison différenciée de ces deux syntagmes et de leur valeur heuristique pour penser l’émancipation. Elles présentent une série de propositions analytiques conduisant à la nécessaire distinction entre la nature normative de la notion de diversité et le fait social que constitue l’hétérogénéité intragroupe – pour tout groupe social. Ce faisant, elles se penchent sur la complexité du concept de résistance et rappellent la part ternaire de tout rapport de domination.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".