Bibliographic record
Abstract
Le système de santé au Canada doit composer avec une pénurie de ressources principalement tributaire de l’insuffisance du financement. Le contexte de pénurie implique que l’on doive faire face à des choix difficiles en ce qui a trait à l’allocation de ces ressources limitées que nous déciderons d’investir (ou non) dans tel domaine de soins, tel établissement, tel traitement ou tel patient. En vue de mieux saisir la nature de ces questions d’allocation, il s’agit dans un premier temps de bien comprendre que la gestion du système de santé implique trois paliers décisionnels : gestionnaires d’hôpitaux, administrateurs des régies régionales et ministres provinciaux. En second lieu, en raison de la portée sociale de ces décisions, de la nature éminemment éthique des enjeux et de la complexité structurelle du système, il importe de favoriser une plus grande transparence au sein des processus décisionnels et de promouvoir la discussion publique afin d’établir des normes cohérentes et rigoureuses en ce qui a trait aux critères de l’allocation des ressources.
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 | 0.025 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".