Étude de l'effet des programmes éducatifs sur les comportements de dons : comparaison entre le Québec et le Canada anglophone
Bibliographic record
Abstract
« Le présent rapport expose les résultats d’une étude menée par l’École de gestion de l’Université de Sherbrooke sur les comportements philanthropiques au Québec. Les données disponibles montrent un écart marqué entre le Québec et le reste du Canada : malgré des niveaux de revenu comparables, les Québécois donnent moins fréquemment et en moindre proportion. En 2022, par exemple, le don annuel médian était de 150 $ au Québec comparativement à 380 $ au Canada, et les dons représentaient 0,3 % du revenu total dans la province, contre 0,7 % à l’échelle nationale. Cette différence persistante soulève des interrogations sur les mécanismes sociaux et éducatifs susceptibles d’influencer durablement les comportements de don, et c’est précisément dans ce contexte que la Fondation de la famille Léger a sollicité notre équipe de recherche. [...] »
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".