Bibliographic record
Abstract
The Canada Health Act (CHA) was adopted in 1984, to shore up a health-care system conceptualized in the 1960s. Under the CHA, universal coverage is limited to "medicallynecessary" hospital and physician services, to the exclusion of vital goods and services such as outpatient pharmaceuticals, dental care, long-term care, and many mental health services. Inequities resulting from these gaps in public coverage are partly to blame for pushing Canada's health system to the bottom ofrecent international rankings. But there is more to modernizing Canada s health care system, we argue, than filling these gaps in universal coverage. Every major health system review undertaken in Canada over the past decade has ended with a call for greater accountability, and rightly so: accountability is arguably the sine qua non of high-performing health systems. Whereas many countries have established open and rigorous processes for evaluating health goods and services, targeting public spending on those that deliver the biggest bang for buck, Canada's governance mechanism for defining the medicare basket is passive, opaque and only tenuously evidence-driven. A move to expand medicare's scope of coverage must be accompanied by improvements in this type of accountability
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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 | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".