Slaves to economists? A Canadian's view of the Australian health care system
Bibliographic record
Abstract
AN EXPERT IS DEFINED as someone from out of town ? with slides. In health care, such experts also have a tendency to make cross-national comparisons on the basis of a short visit, a few conversations, and a desire to indicate ?lessons learned?.1 In that time-honoured tradition, on the basis of a visit to Melbourne to address the Victorian Healthcare Association, coupled with visits to several local hospitals, this Canadian identified several potential problems arising from Australia?s approach to the public?private mix of hospital services. As Keynes noted, ?The ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood. Indeed the world is ruled by little else. Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist.?2 Over the past decades, many health care reformers have urged change ? with varying degrees of success ? based on a set of ideas that markets are always right, that competition is both necessary and sufficient for efficiency, and that private is superior to public. One consequence has been a push for a greater role for private delivery of health care services. This is currently hotly contested in Canada, with Australia providing either an exemplary example or a cautionary tale, depending upon ideological proclivities. I was therefore interested in learning more from Australians as to areas of success or failure of the public?private mix in Australia, and this paper highlights my observations.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.021 | 0.030 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".