Equity in public health standards: a qualitative document analysis of policies from two Canadian provinces
Bibliographic record
Abstract
INTRODUCTION: Promoting health equity is a key goal of many public health systems. However, little is known about how equity is conceptualized in such systems, particularly as standards of public health practice are established. As part of a larger study examining the renewal of public health in two Canadian provinces, Ontario and British Columbia (BC), we undertook an analysis of relevant public health documents related to equity. The aim of this paper is to discuss how equity is considered within documents that outline standards for public health. METHODS: A research team consisting of policymakers and academics identified key documents related to the public health renewal process in each province. The documents were analyzed using constant comparative analysis to identify key themes related to the conceptualization and integration of health equity as part of public health renewal in Ontario and BC. Documents were coded inductively with higher levels of abstraction achieved through multiple readings. Sets of questions were developed to guide the analysis throughout the process. RESULTS: In both sets of provincial documents health inequities were defined in a similar fashion, as the consequence of unfair or unjust structural conditions. Reducing health inequities was an explicit goal of the public health renewal process. In Ontario, addressing "priority populations" was used as a proxy term for health equity and the focus was on existing programs. In BC, the incorporation of an equity lens enhanced the identification of health inequities, with a particular emphasis on the social determinants of health. In both, priority was given to reducing barriers to public health services and to forming partnerships with other sectors to reduce health inequities. Limits to the accountability of public health to reduce health inequities were identified in both provinces. CONCLUSION: This study contributes to understanding how health equity is conceptualized and incorporated into standards for local public health. As reflected in their policies, both provinces have embraced the importance of reducing health inequities. Both concepualized this process as rooted in structural injustices and the social determinants of health. Differences in the conceptualization of health equity likely reflect contextual influences on the public health renewal processes in each jurisdiction.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.019 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 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".