La Grande Noirceur canadienne-française dans l’historiographie et la mémoire québécoises : Revisiter une interprétation convenue
Bibliographic record
Abstract
Plus qu’une periode historique bien definie (des annees 1936 aux annees 1950), la Grande Noirceur represente une epoque repoussoir. Elle est un mythe constitutif du grand recit moderne quebecois. Elle serait par ailleurs une modalite de gestion du passe, qui cherche a prendre en compte le legs dit autoritaire d’une periode historique. Ses representations mettent en scene une « mythistoire » qui, tout en mimant l’histoire savante, propose un recit dominant reproduit de generation en generation. Cet article examine a la fois le discours qui a elabore et propage l’idee de la Grande Noirceur, et celui qui a cherche a remettre en question sa veracite et sa portee historique. Son but n’est pas tant d’evaluer le degre de noirceur de la periode precedant la Revolution tranquille, que de decrire les jalons de la construction sociohistorique de la rupture des annees 1960 et de la deconstruction, plus recente, de ce recit encombre de mythologies de toutes sortes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".