Bibliographic record
Abstract
Canadians view their healthcare – recognized throughout the world as an exemplary system – as iconic and integral to their identity. In Toward the Health of a Nation Leslie Boehm recounts the first seventy years in the life of one of the foundations of Canada's healthcare system, the Institute of Health Policy, Management and Evaluation at the University of Toronto. Boehm – a graduate of IHPME, and an instructor there throughout his career – charts the institute's history from its inception in 1947 as the Department of Hospital Administration to the present day. The first program of its kind in Canada, and one of the few in the world, the school was founded at a time when the issue of healthcare was becoming a significant part of national and provincial discussions and policies. Initially concentrating on hospital management and professional degrees, it has expanded to offer academic degrees and facilitate important research into health systems, policies, and outcomes. In Toward the Health of a Nation Boehm demonstrates the excellence of the program, its faculty, and its graduates, as well as their accomplishments in major government initiatives and royal commissions. In the seventy years since IHPME's inception healthcare has grown to become a major part of government and business activity, and it will only increase in coming years. An in-depth history of a major program in graduate health education, Toward the Health of a Nation highlights how important healthcare is to a modern, functional society.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".