Enseigner la Terreur en plurilinguisme et interculturalité : quelles implications pour l’approche historienne des relations entre France, îles britanniques et Amérique du Nord à la fin du XVIIIe siècle ?
Bibliographic record
Abstract
Partant des manuels d’histoire qui ont bâti et/ou reconstruit l’identité nationale, l’article se concentre sur l’évocation de l’époque révolutionnaire française appelée « Terreur » telle qu’elle apparaît, ou non, dans les nouveaux manuels qui depuis 2005 se sont ouverts à l’histoire mondiale. Il existe plusieurs filières et traitements appropriés à l’âge et au niveau de compréhension des écoliers, jusqu’à la terminale. Dans les classes d’apprentissages de l’histoire en langue étrangère (très majoritairement l’Anglais), la révolution de 1689 en Angleterre, la révolution américaine, la révolution française et la révolte/révolution de St. Domingue prennent des reliefs bien différents du programme scolaire centré sur la France et les départements d’Outremer. L’article évalue les divers équilibres apportés aux manuels et la part de créativité qui revient aux enseignants et aux élèves.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".