Bibliographic record
Abstract
Transcript: Listen to today's Commentary Introduction: Who speaks best for health care: Paul Martin or the provincial premiers? Vivian McAlister is a transplant surgeon and a professor of surgery in London, Ontario. On Commentary, he says move over Ottawa..the provinces should take the lead in improving medicare. Vivian McAlister: During last month's election campaign Paul Martin set himself up as the saviour of medicare. He was reinforcing an old theme: that Ottawa must keep a close eye on the provinces lest they experiment - looking for different ways to provide health care. The prime minister conveniently ignored the fact that his 1995 budget that stripped billions of dollars from health care did more damage to the system than any province. Nor did he recognize that it's the provinces that are the truly creative force in the delivery of health care. I'm a doctor. I've worked in small and large hospitals in several provinces. Before I came to Canada, I practised in the British National Health system and in the Irish two-tier system. And I can tell you Canadian health care is second to none. We provide the best care to the most people, regardless of income or remoteness of residence, and it was the provinces that brought us here. Saskatchewan led the way with public health insurance. The portability and universal access provisions of the Canada Health Act ensure that provincially-delivered health care is practical in a modern Canada. Today portability allows patients to go from one province to another in search of the best medical care. The resulting competition among provinces provides a stimulus for continuous growth. When one province provides a new type of surgery or pays for a new treatment, other provinces are eventually forced to follow suit. It's the one difference that allows the Canadian system to succeed where the centralized British system has failed. The ironic result of the budget cuts of 1995 was to impose greater uniformity on the system. The loss of innovation was worse than the actual loss of funds. Mr. Martin's platform, now and at the next election, should be to facilitate health-care delivery by the provinces. The people of the provinces will deal with their own governments if the delivery is flawed. Canada's flaw is that the federal government collects the taxes that should be going to the provinces for health-care delivery. This anomaly restricts Ottawa's health care spending to trendy capital budgets and diverts money from desperately needed operating funds. Instead of imposing uniformity, why doesn't Ottawa enable the spending of revenues on health-care delivery that could spawn more innovation at the provincial level. It could help Ontario, for example, meet the challenge of its new health-care premium by offering a federal tax credit to offset the cost to individuals. In this way Mr. Martin might build his legacy by finding a way for provincialism to flourish in the Canadian confederation. It is, after all, how the Liberal Party started. For Commentary, I'm Vivian McAlister in London.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.029 | 0.009 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".