Based Pricing, and Drug R&D: A Critique of the National Forum on Health’s Recommendations for
Bibliographic record
Abstract
ceutique au Canada. Ces recommandations suggèrent de se diriger vers un programme d’assurance-médicaments à couverture universelle et financé par le secteur public. De plus, elles supportent le “reference-based pricing” comme méthode de contrôler des coûts du programme et demandent aux compagnies pharmaceutiques de retour-ner une portion de leurs fonds de recherche aux agences nationales distribuant des bourses de recherche. Cet article présente une évaluation critique des recommandations en mettant l’emphase sur la possibilité qu’elles mènent à long terme à des réductions dans les dépenses relatives aux médicaments et à la santé au Canada. In February 1997, the Canadian National Forum on Health presented its recommendations for a pharmaceutical policy for Canada. These recommendations include moving toward a universal coverage, publicly funded drug plan; support for reference-based pricing as a method of containing drug plan costs; and requiring that pharmaceutical companies turn over a portion of their research funds to the national research granting agencies. This paper provides a critical assessment of these policy recommendations, with a focus on whether they are likely to achieve long-term reductions in pharmaceutical and health-care expenditures in Canada.
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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 | 0.057 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.020 | 0.023 |
| 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".