Mixité, modernité et déracinement, des freins à la transmission de la langue dans deux familles amazighes
Bibliographic record
Abstract
Recueillir le récit des premiers intéressés, les Amazighs, est une voie privilégiée lorsqu’il s’agit d’analyser le fait linguistique. Quelles sont les raisons de la perdition de leurs langues aujourd’hui? Il en va de la présente étude de dévoiler certaines de ces raisons, en confrontant le récit et la réalité vécue par deux familles appartenant à des communautés amazighes distinctes, les Toulalyines et les Souassas. Bien que la construction de l’État ait joué un rôle important dans le fléchissement de leurs langues, on pourrait se demander quelle est la nature des faits internes à ces familles ayant accentué cette réalité. L’étude démontre que la mixité, l’attraction vers la modernité ainsi que le déracinement contribuent à la perdition de la langue.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".