Transformation des dynamiques minoritaires, paradigmes sociolinguistiques et émotions
Bibliographic record
Abstract
L’étude des minorisations linguistiques traverse la sociolinguistique des contacts de langues. Quel que soit le contexte culturel et social envisagé, la domination linguistique relève de phénomènes d’exclusion, de rejet de l’autre, mais aussi de son propre groupe d’appartenance. Or, il semble que la description et l’analyse de ces différentes réactions face à la domination s’actualisent dans des moments historiques particuliers, socialement et scientifiquement inscrits. Cet article vise à montrer comment la sociolinguistique a décrit ces rapports de domination depuis les années 1970, quelles notions elle a mobilisées en regard des idéologies sociales et scientifiques considérées, telle la diglossie conflictuelle, et comment l’on pourrait appréhender aujourd’hui ces rapports de domination à l’aune de sentiments et processus individuels ou sociaux, telles la honte et l’agentivité, plus en lien avec l’individuation de nos sociétés contemporaines.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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 | 0.001 |
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 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".