La minorisation linguistique, entre discrimination et domination symbolique. Différences et enjeux de deux lectures des inégalités
Bibliographic record
Abstract
Lorsque l’on évoque des situations de minorisation linguistique, il est courant de les associer à des processus de domination ou de discrimination, à tel point que ces termes peuvent sembler indissociables, voire quasiment synonymes. Cette contribution propose cependant de mettre en évidence ce qui sépare une approche des faits de minorisation inscrite dans une réflexion critique sur la « domination » d’une lecture de la minorisation comme processus de discrimination. L’analyse tente en particulier de saisir ce que la notion de discrimination véhicule comme conception particulière des problèmes sociaux et ce que sa diffusion actuelle doit à sa proximité avec certains traits de la vision du monde social qui tend à s’imposer aujourd’hui.
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How this classification was reachedexpand
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".