Bibliographic record
Abstract
Cet article décrit un nouveau cours universitaire de français oral L2 et tente d’en justifier la méthode et le corpus. Ayant relevé certains achoppements de l’enseignement de l’oral par les méthodes didactiques contemporaines, l’auteur propose de reconnaître la nature seconde (W. Ong) et performancielle (P. Zumthor) d’une oralité plus littéraire, cultivée par ce cours dont l’objectif est de travailler particulièrement l’accent et la phonostylistique. Différents types de performances à haute voix y mettent en valeur des textes tirés de romans, poésies, contes, discours, dialogues de films. En devoirs, les étudiants les partagent en ligne, puis leurs performances sont évaluées et commentées en mode asynchrone ; le temps de classe sert à des ateliers d’écoute, d’orthoépie et de phonostylistique. L’auteur fournit en exemple la consigne décrivant un devoir de « Commentaire en voix hors champ ».
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".