Les determinants individuels de la participation electorale aux elections generales quebecoises de 2018
Bibliographic record
Abstract
Le présent rapport de recherche s’inscrit en continuité avec les travaux antérieurs qui tentent de comprendre les causes de la participation électorale aux élections québécoises. L’étude cherche parallèlement à identifier les sources de l’abstentionnisme d’un point de vue quantitatif. Le phénomène ayant déjà fait l’objet d’analyses antérieures chez les jeunes (Dostie-Goulet et al., 2012) ainsi que dans une perspective plus qualitative (Steben-Chabot, 2016), la présente analyse vient complémenter les connaissances à ce sujet. Finalement, 10 ans après le scrutin de 2008 qui a fait l’objet d’une analyse par des chercheurs de la Chaire de recherche sur la démocratie et les institutions parlementaires (Gélineau et Morin-Chassé, 2009), ce rapport met en perspective les résultats obtenus lors de cette élection avec ceux de l’enquête administrée en 2018.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".