La hiérarchisation des accents en français, entre représentations et réalité : étude de perception d’accents natifs et non natifs en Suisse romande
Bibliographic record
Abstract
La parole accentuée a toujours suscité des réactions plus ou moins vives. La mondialisation actuelle favorise les échanges intergroupes et multiplie les situations de communication exolingue, confrontant les auditeurs à une multitude d’accents, natifs ou non. Dans ce travail, nous présentons une étude de perception de différents accents natifs et non natifs en français menée auprès de trois groupes d’auditeurs francophones natifs qui devaient évaluer la convenance des locuteurs pour trois postes différents sur la base d’une écoute à l’aveugle d’extraits de parole spontanée. Nos résultats montrent une importante hiérarchisation des accents en français, qui n’oppose pas accent natif et accent non natif, mais qui semble indiquer qu’il existe une évaluation des accents en fonction de leur valeur sociale et des représentations auxquelles les auditeurs tendent à les associer.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".