Putting National Pharmacare on the Federal Agenda
Bibliographic record
Abstract
In June 2018, the Federal Government of Canada created an Advisory Council on the Implementation of National Pharmacare, scheduled to report one year later on the best strategy to implement such a program and give Canadians access to affordable prescription drugs outside of the hospital. The current state of coverage through employer-sponsored plans and public plans conditional on income and age is increasingly perceived as unfair and inefficient. The Council used a mixture of expert consultations, an online survey and discussion forums for the general public to explore three options: a universal public plan, a catastrophic spending plan, or a patching of current coverage to include the non-covered. Creating such a Council was seen by the government as a solution for navigating a complex policy problem with difficult federal-provincial dimensions. Le gouvernement fédéral canadien a créé en juin 2018 un Conseil consultatif sur la mise en œuvre d’un régime national d’assurance médicaments, dont le rapport sur la meilleure stratégie pour mette en œuvre un tel régime et permettre aux Canadiens d’accéder à des médicaments abordables hors de l’hôpital est attendu un an après. La situation présente couvrant les individus à travers une combinaison de plans d’employeurs et de plans publics sous condition de revenu et d’âge est de plus en plus perçue comme injuste et inefficace. Le Conseil devra donc explorer trois options, en s’appuyant sur des consultations d’experts, un sondage en ligne, et des forums de discussion pour le grand public : un régime public universel, un régime couvrant les dépenses catastrophiques, et un régime modeste offert à ceux n’ayant pour l’instant aucune couverture. La création de ce Conseil était vue par le gouvernement comme une solution pour négocier une question délicate affectant l’équilibre des prérogatives provinciales et fédérales.
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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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.039 | 0.034 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".