Études de cas portant surunesélection de pays de l’OCDE : Canada
Bibliographic record
Abstract
Le gouvernement fédéral canadien produit et utilise des informations relatives au rendement des programmes depuis la fin des années 70, époque à laquelle il a instauré sa première politique d’évaluation. Au cours des 30 dernières années, ces informations ont été utilisées à deux fins essentielles – d’abord pour assurer la transparence des informations communiquées au Parlement; ensuite pour appuyer les décisions d’affectation des ressources au sein de l’Exécutif. Ces derniers temps, les responsables de la mesure de la performance se sont surtout efforcés de soutenir la gestion et les communications au Parlement, et seulement dans une moindre mesure de guider les décisions d’affectation et de réaffectation des dépenses. Ce dosage évolue cependant, et le gouvernement actuel a mis l’obligation de rendre compte et l’optimisation des ressources des programmes au coeur de son programme de gestion.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".