Les grands courants de l’enseignement de la littérature en classe du secondaire au Québec
Bibliographic record
Abstract
Au lieu d'un resume, voici un bref extrait de cet article: La litterature a toujours occupe une place importante a l’ecole dans les systemes scolaires francophones. Reserves principalement aux classes du secondaire et consideres comme le modele d’ecriture qu’il faut imiter, les textes litteraires des « grands auteurs » servent surtout, jusqu’a la fin du XIXe siecle, a apprendre a ecrire bellement (Simard 2001; Dufays, Gemenne et Ledur; Galarneau). Depuis la fin du XIXe siecle jusqu’au milieu du XXe, la litterature devient egalement la base de la formation de l’identite culturelle et sert a faconner la memoire collective (Rouxel; Dufays, Gemenne et Ledur; Melancon, Moisan et Roy). Les annees 1960 voient cependant naitre une crise de l’enseignement en general et de l’enseignement de la litterature en particulier. Autant au Quebec qu’en France, on se questionne sur les buts et les finalites de cet enseignement et on cherche a le redefinir. Plusieurs tentatives de renovation voient le jour. Differentes approches et divers modeles se cotoient en classe, souvent d’origine heterogene, et parfois meme contradictoire. A la notion de l’enseignement de la litterature se substitue peu a peu celle d’enseignement de la lecture des textes litteraires (Rosier 2002).
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".