Identités, économie et territoire : la mesure des identités au Québec et la Question Moreno
Bibliographic record
Abstract
Résumé L’objectif de ce texte est de présenter comment les chercheurs ont mesuré l’identité québécoise, surtout depuis le début des années 1960. Diverses mesures ont été utilisées dans les enquêtes d’opinion chacune reflétant en partie le contexte social et politique d’une époque. Depuis la fin des années 1990, l’indice de Moreno, comme mesure dualiste de la réalité canadienne, a contribué à relancer les débats autant sur la spécificité de l’État canadien comme entité multinationale qu’à redéfinir les liens d’appartenance entre les Québécois et les Canadiens des autres provinces. Cette redéfinition des identités s’inscrit également dans un contexte économique nord-américain qui a profondément transformé l’identité continentale des Québécois.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".