Esyllt W. Jones, James Hanley, and Delia Gravus, <i>Medicare’s Histories: Origins Omissions, and Opportunities in Canada</i>
Bibliographic record
Abstract
The main title of this edited volume is a reference to the programme of universal health coverage (UHC) in Canada which is colloquially known as Medicare. This federal–provincial programme is sometimes confused with the similarly named universal health insurance scheme in Australia and contributory health insurance programme for the elderly in the USA. Eschewing traditional political history, the volume brings together a generation of scholars steeped in the methods of contemporary social history as well as holding more critical views on the evolution of the welfare state. Most notably, the authors examine Medicare through the experiences of those providing or receiving the services rather than the policy decision-makers at the top of the system. For non-Canadian readers, Medicare in Canada has multiple dimensions. It is a set of values enshrined in the Canada Health Act that embrace a strong form of universality (free access on uniform terms and conditions and no user fees) combined with decentralised administration by ten provincial and three territorial governments. The providers of services vary from independent, for-profit professionals (e.g. most doctors) to salaried health professionals (e.g. most nurses) and support staff working in public and private facilities. The system is bound together through the portability of coverage and other national standards which are upheld by subnational governments to avoid clawbacks from a federal health transfer.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 0.015 |
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".