Enseignement interdisciplinaire des <i>Trois Mousquetaires</i>
Bibliographic record
Abstract
Cet article propose un mode d’enseignement du mythe littéraire à des apprenants en Français Langue Etrangère. Tenant compte de la barrière linguistique, du profil des étudiants et de l’immense corpus du mythe littéraire, il suggère un moyen de faire « entrer » les apprenants dans ce dernier : par le héros. Après avoir restreint la définition du mythe en insistant sur le rôle essentiel du personnage central, il avance une approche théorique basée sur les discussions de cours et sur les travaux écrits. This article offers a way of teaching the literary myth to French as a Second Language students. As it takes into account the language barrier, the learners’ profiles and the vast corpus of the literary myth, it suggests a medium to make students « enter » the myth. : through the hero. While insisting on the essential role of the central character, this article reduces the definition of the literary myth, and it offers a theoretical approach, which is based on class discussions and written assignments.
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 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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".