Enquête canadienne sur le don, le bénévolat et la participation, 2010 [Canada] : Composante des dons
Bibliographic record
Abstract
L'Enquête canadienne sur le don, le bénévolat et la participation (ECDBP) est le résultat d'un partenariat de ministères fédéraux et d'organisations du secteur bénévole qui comprend Imagine Canada, Patrimoine canadien, Santé Canada, Ressources humaines et Développement social Canada, l'Agence de santé publique du Canada, Statistique Canada et Bénévoles Canada. Cette enquête est une source importante d'information sur le comportement contributif des Canadiens au sujet des dons, des activités bénévoles et la participation. L'ECDBP poursuit trois objectifs : 1) recueillir des données à l'échelle nationale pour combler une lacune en matière de renseignements sur les comportements contributifs de particuliers, y compris le bénévolat, les dons à des organismes de bienfaisance et la participation; 2) fournir des données fiables et ponctuelles au Système de comptabilité nationale; 3) communiquer à la fois au public et aux secteurs bénévoles les décisions en matière de politiques et de programmes qui ont trait aux secteurs de bienfaisance et de bénévolat.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.016 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".