The Roots of North America's First Comprehensive Public Health Insurance System
Bibliographic record
Abstract
The Canadian province of Saskatchewan in 1944 it inherited a long tradition of “socialized“ medicine in many rural regions. However, urban medicine was based on fee-for-service payment of physicians and no private health insurance. In crafting North America’s first public health insurance system, the government built on the rural medical infrastructure already in place by expanding a rural salaried system of physician payment and successfully promoted a regional comprehensive insurance system piloted in a southern region of the province. However, major demographic shifts from countryside to city during the 1950s, burgeoning physician supply, increased immigration of physicians into the provinces’ cities, and aggressive expansion of urban-based private insurance for physician services into rural regions, shifted the balance of medical power away from rural towards urban centers in the province. The increasing resistance, by the medical profession, to health-care reform in Saskatchewan in the 1950s must be considered within a geographic framework as rural regions of the province became the major battleground between government and insurance third party payers. While historical comparisons should not be overstated, re-visiting this struggle may be useful in the current era in which the pressure for privatization of the medical system in Canada appear to be growing.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".