De plus en plus inquiets : qui sont les Québécois qui considèrent le français comme menacé et quelles en sont les conséquences électorales?
Bibliographic record
Abstract
Résumé L’usage du français au Québec est en recul (Commissaire à la langue française, 2024a; Statistique Canada, 2022), contribuant à la perception que la langue française est menacée. Cette situation soulève plusieurs questions quant à l’évolution temporelle de l’opinion publique relativement à cette perception et ses conséquences politiques. Dans cet article, nous examinons d’abord l’évolution de l’opinion publique concernant la perception selon laquelle la langue française serait menacée afin de quantifier les changements survenus entre 1993 et 2024. Ensuite, nous analysons les déterminants de ce sentiment de menace. Enfin, nous examinons les conséquences électorales en politique fédérale. Les résultats illustrent (1) qu’une forte majorité des citoyens estime que le français est menacé, (2) cette proportion a nettement augmenté à travers le temps et (3) ce sentiment est lié au choix électoral. Ces conclusions suggèrent que les enjeux linguistiques constituent un facteur crucial pour mieux saisir la politique québécoise et canadienne.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".