La flexion postverbale <i>-ont</i> en français acadien: une analyse sociolinguistique
Bibliographic record
Abstract
Nous présentons une analyse sociolinguistique de la flexion postverbale -ont 3pl en français acadien du nord-est du Nouveau-Brunswick. Il est démontré que la variation dans l'emploi de cette désinence traditionnelle est explicable d'abord par des facteurs extralinguistiques, plus particulièrement le réseau social. Cependant, le maintien de -ont est aussi conditionné par un phénomène interne à la langue, soit la contribution de cette désinence à la régularité des oppositions radicaux singulier/pluriel et les formes 3sg /3pl dans les paradigmes de verbes. Plus la présence de -ont permet d'optimaliser ces oppositions, plus la tendance à retenir cette flexion est importante. En somme, les formes telles que i-pouvont, i-voulont et i-buvont—qui permettent d'affirmer l'identité et la position sociale du locuteur au sein de sa communauté et d'optimaliser l'emploi des formes dans le paradigme verbal—ont des probabilités plus élevées d'être retenues.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".