Single Payers, Multiple Systems: The Scope and Limits of Subnational Variation Under a Federal Health Policy Framework
Bibliographic record
Abstract
In political discourse, the term "single-payer system" originated in an attempt to stake out a middle ground between the public and private sectors in providing universal access to health care. In this view, a single-payer system is one in which health care is financed by government and delivered by privately owned and operated health care providers. The term appears to have been coined in U.S. policy debates to provide a rhetorical reference point for universal health insurance other than the "socialized medicine" of state-owned and -operated health care providers. This article, like others in this special issue, is meant to provide a more nuanced view of single-payer systems. In particular, it reviews experience in the prototypical single-payer system for physician and hospital services: the Canadian case. Given Canada's federal governance structure, this example also aptly illuminates the scope and limits of subnational variation within this single model of health care finance. And what it demonstrates in essence is that the very feature that defines the single-payer prototype -- the maintenance of independent providers remunerated by a single public payer in each province -- also leads to a set of profession-state bargains that define the limits of variation.
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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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".