Bibliographic record
Abstract
Les leaders en santé du Canada affrontent une foule de défis dans le secteur de la philanthropie en santé. Ces défis ne se limitent pas à l'aspect pratique des mesures à prendre pour réussir, mais également à des questions éthiques. Est-ce que la collecte de fonds est acceptable si elle donne lieu à des partenariats avec des entreprises qui participent à l'apparition de maladies causées par le mode de vie? Quand la reconnaissance méritée envers les donateurs ou les bénévoles dépasse-t-elle les bornes et favorise-t-elle un accès privilégié aux soins? Les décisions éthiques de la philanthropie en santé doivent opposer les témoignages de reconnaissance ou les partenariats avec les donateurs au bien public, qui s'inscrit dans le mandat des établissements de santé et qui fait partie et des obligations fiduciaires des hôpitaux et des cliniciens envers les patients.
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 | 0.031 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.083 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".