Which appropriate framework to study and describe philanthropic foundations in Canada?
Bibliographic record
Abstract
L’article répond à une question centrale : quel cadre d’analyse serait le plus pertinent pour comprendre le secteur des fondations subventionnaires canadiennes ? Ils précisent d'abord les enjeux normatifs de cet exercice a priori simplement descriptif. Puis, afin de répondre à la question centrale, les auteurs présentent en premier lieu le secteur en utilisant les informations et cadres d'analyse de l'Agence du Revenu du Canada. Puis ils font son portrait en détaillant les rôles pris, et parfois formalisés théoriquement, par les fondations. Enfin, dans un troisième temps, les auteurs font usage des trois principaux cadres théoriques qu’ils ont recensés dans la littérature scientifique pour analyser les fondations. Les auteurs concluent l’article en analysant les interrelations, théoriques et pratiques, de ces trois grilles d'analyse.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".