Understanding action on the social determinants of health: a critical realist analysis of in-depth interviews with staff of nine Ontario public health units
Bibliographic record
Abstract
BACKGROUND: Addressing the social determinants of health (SDH) is identified as a role for local public health units (PHUs) in the province of Ontario. Despite this authorization to do so there is wide variation in PHU practice. In this article we consider the factors that shape local PHU action on the SDH through a critical realist analysis. METHODS: Interviews with Medical Officers of Health (MOHs) and lead staff from nine PHUs in Ontario identify the structures and powers that allow PHUs to address the SDH as well as the many factors that either activate or inhibit these structures and powers. RESULTS: We found that personal backgrounds and attitudes of MOHs and leading staff people as well as local jurisdictional characteristics shape whether and how PHUs carry out SDH-related activities. CONCLUSIONS: Action on the SDH is a result of a complex interplay of micro-, meso- and macro-level factors that requires recognition of the contested nature of public health, presence of Ministry of Health mandates, local jurisdictional characteristics, and politics. The most effective way to assure PHU action on the SDH is for the Ministry of Health and Long-Term Care to mandate such activities and develop accountability mechanisms that assure implementation.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.025 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".