Addressing the non-medical determinants of health: A survey of Canada’s health regions", Canadian
Bibliographic record
Abstract
Background: The Canadian health system is undergoing reform. Over the past decade a prominent trend has been creation of health regions. This structural shift is concurrent with a greater emphasis on population health and the broad determinants of health. In parallel, there is a movement toward more intersectoral collaboration (i.e., collaboration between diverse segments of the health system, and between the health system and other sectors of society). The purpose of this exploratory study is to determine the self-reported level of internal action (within regional health authorities) and intersectoral collaboration around 10 determinants of health by regional health authorities across Canada. Methods: From September 2003 to February 2004, we undertook a survey of regional health authorities in Canadian provinces (N=69). Using SPSS 12.0, we generated frequencies for the self-reported level of internal and intersectoral action for each determinant. Other analyses were done to compare rural/suburban and urban regions, and to compare Western, Central and Eastern Canada. Results: Of the 10 determinants of health surveyed, child development and personal
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".