Défendre sa/ses langues : quels mots pour le dire ? Le cas de l’amazigh au Maroc
Bibliographic record
Abstract
"Le traitement des langues au Maroc est fortement associé aux aspects politiques, idéologiques, éducatifs, identitaires que l’on peut observer dans un pays marqué par une dynamique sociale assez soutenue. La valorisation d’une langue ou sa minoration va de pair avec l’attitude qui prévaut à l’égard des langues de la communication quotidienne et de la culture populaire dans ses versants arabophone et amazighophone. Le fossé n’a pas cessé de se creuser depuis très longtemps, entre une culture savante, élitiste, dominante et une culture dite "de masse", reléguée au second plan, dépréciée. La distribution des biens culturels et linguistiques participe d’un rapport de force régi par des considérations que les différents antagonistes rattachent à différentes sphères : identitaire, culturelle, économique, religieuse, etc. [...]"
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".