Bibliographic record
Abstract
En 2012 puis en 2014, d’importants changements à la Loi électorale québécoise ont transformé la façon par laquelle les partis politiques se financent au Québec. La contribution maximale individuelle a été radicalement réduite et le financement public des partis politiques a été augmenté. Cette étude de cas quantitative tente de mesurer l’impact de cette réforme sur la participation électorale, les dépenses des partis en circonscription et l’offre politique partisane. À l’aide de la régression linéaire multiple, nous montrons qu’un effet sur la participation peut être possible. Nous montrons également que la réforme ne semble pas avoir affecté la façon par laquelle les partis se financent en circonscription. À l’aide de l’analyse textuelle automatisée, nous montrons que l’offre partisane a convergée de façon significative entre 2003 et 2014. Ce mémoire s’inscrit dans un axe de recherche général de la Chaire de recherche sur la démocratie et les institutions parlementaires.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".