Le mécanisme des stratégies de réparation en phonotactique générative et la diphtongaison en français montréalais
Bibliographic record
Abstract
Cet article examine l’action des stratégies de réparation en phonotactique générative, modèle où la phonologie est constituée de conditions de bonne formation et de stratégies de réparation consistant en la substitution, en l’insertion ou en l’effacement d’un segment (et possiblement aussi en l’inversion). Ces conditions (CBF) ne gouvernent que des alternances automatiques et globales; les autres alternances relèvent soit de la morphologie, soit de la stylistique. Dans un premier temps sont examinés des exemples de CBF dans diverses langues afin d’identifier les facteurs qui déterminent le choix de la statégie et de la cible. Ces facteurs semblent être le respect de l’identité phonologique du segment et le caractère minimal de la stratégie. Dans un second temps est proposée une description de la diphtongaison du français montréalais au moyen de l’interaction de diverses CBF.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".