Analyse discursive des manuels d’histoire de 1967 à 2012 : Coup d’œil sur vingt évènements historiques du Québec
Bibliographic record
Abstract
Résumé Cet article interroge la représentation de vingt grands personnages historiques du Québec au sein des manuels découlant des trois principaux programmes d’histoire du ministère de l’Éducation du Québec ayant vu le jour depuis sa création, soit le programme de 1967, de 1982 et de 2007. L’objectif ici est de relever la présence des idéologies politiques et identitaires au sein de ces représentations, ainsi que leurs continuités et leurs ruptures. Pour ce faire, nous joignons à l’analyse de contenu qualitative le codage appliqué à l’analyse de discours, lequel nous permet de procéder, dans un dernier temps, à une analyse statistique. Summary This article examines the representation of twenty great figures in Quebec’s history, found within textbooks from the three main programs of the Department of History of Education of Quebec that have emerged since its creation (1967, 1982, 2007). The aim is to detect the presence of political ideologies and identity within these representations and their continuities and conclusions. To do this, we join to the qualitative content analysis with the coding applied to discourse analysis, which allows us to carry out further statistical analyses.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".