Regard sur Québec, les blocs régionaux et l’ascension de la CAQ (2016-2018)
Bibliographic record
Abstract
Aux élections de 2018, la Coalition Avenir Québec (CAQ) a brisé l’alternance bipartisane entre le Parti québécois (PQ) et le Parti libéral du Québec (PLQ) en remportant un premier mandat majoritaire. À plusieurs égards, ses positions identitaires et sa percée à Québec dans la circonscription électorale de Louis-Hébert l’avaient consacrée comme option de rechange au gouvernement libéral. Cet article propose de se pencher plus profondément sur l’importance stratégique de la grande région de Québec dans l’écosystème politique québécois, de survoler l’état de la recherche sur la montée de la CAQ, de décrypter la progression du parti de François Legault dans les sondages en 2016-2018 et de revenir sur l’élection partielle de Louis-Hébert, notamment sur son lien avec le débat sur le racisme systémique.
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 | 0.001 | 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 | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".