Evaluating engagement with equity in Canadian provincial and territorial primary care policies: Results of a jurisdictional scan
Bibliographic record
Abstract
Equitable access to primary care is essential to achieving more equitable health outcomes, yet evidence suggests that structurally marginalized populations are less likely to have benefited from varied primary care reforms in Canada. Our objective is to determine how equity is incorporated in public primary care policy and strategy documents across Canada. We conducted string term and snowball searches for provincial/territorial primary care policy documents published between 01 January 2018 and 30 June 2022, extracted the policy objective, and applied a rubric to evaluate each document's engagement with equity. We performed content analysis of the documents which acknowledged inequities and articulated a related policy response. Of the 224 identified documents that discussed primary care policy: 63 (28 %) identified one or more structurally marginalized group(s) experiencing inequities related to primary care, 64 (29 %) identified a structurally marginalized group and articulated a policy response, and 16 (7 %) articulated a detailed policy response to address inequities. Even where policy responses were articulated, in most cases these did not directly address the acknowledged inequities. The absence of measurable goals, meaningful community consultation, and tenuous connections between the policy response and inequities mentioned may help explain persistent inequities in primary care across Canada.
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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 | 0.026 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.025 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".