Tolérance (des différences), purisme et politique linguistique en Slovaquie et en France
Bibliographic record
Abstract
Notre article est divisé en deux parties. L’auteur de la première, Monika Zázrivcová, s’est proposée de réfléchir sur la tolérance en linguistique, en partant de la situation qui éveille actuellement en Slovaquie une vive discussion dans le milieu linguistique (elle est probablement inconnue au public francophone). L’auteur de la deuxième partie, Katarína Chovancová, a essayé de mettre en parallèle deux mesures législatives dans le domaine de la langue en Slovaquie et en France, la loi sur la langue et la loi Toubon, pour tenter une comparaison entre certains aspects des politiques linguistiques mises en place dans les deux pays. Au terme de l'analyse, elle nomme les institutions principales qui ont pour mission d’assurer la mise en place de ces politiques.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".