Achievements and Challenges of Medicare in Canada: Are We There Yet? Are We on Course?
Bibliographic record
Abstract
Health care policy in Canada is based on providing public funding for medically necessary physician and hospital-based services free at the point of delivery ("first-dollar public funding"). Studies consistently show that the introduction of public funding to support the provision of health care services free at the point of delivery is associated with increases in the proportionate share of services used by the poor and in population distributions of services that are independent of income. Claims about the success of Canada's health care policy tend to be based on these findings, without reference to medical necessity. This article adopts a needs-based perspective to reviewing the distribution of health care services. Despite the removal of user prices, significant barriers remain to services being distributed in accordance with need-the objective of needs-based access to services remains elusive. The increased fiscal pressures imposed on health care in the 1990s, together with the failure of health care policy to encompass the changing nature of health care delivery, seem to represent further departures from policy objectives. In addition, there is evidence of increasing public dissatisfaction with the performance of the system. A return to modest increases in public funding in the new millennium has not been sufficient to arrest these trends. Widespread support for first-dollar public funding needs to be accompanied by greater attention to the scope of the legislation and the adoption of a needs-based focus among health care policymakers.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".