Expanding health care coverage in Canada: a dramatic shift in the debate
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has shifted the health policy debate in Canada. While the pre-pandemic focus of policy experts and government reports was on the question of whether to add outpatient pharmaceuticals to universal health coverage, the clustering of pandemic deaths in long-term care facilities has spurred calls for federal standards in long-term care (LTC) and its possible inclusion in universal health coverage. This has led to the probability that the federal government will attempt to expand medicare as Canadians have known it for the first time in over a half century. However, these efforts are likely to fail if the federal government relies on the shared-cost federalism that marked the earlier introduction of medicare. Two alternative pathways are suggested, one for LTC and one for pharmaceuticals, that are more likely to succeed given the state of the Canadian federation in the early 21st century.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.011 | 0.011 |
| 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".