Public priorities for primary care in Canada
Bibliographic record
Abstract
OBJECTIVE: To present recommendations from 5 provincial reference panels conducted as part of the OurCare initiative, the largest-ever national effort to engage the public about the future of primary care in Canada. COMPOSITION OF THE COMMITTEE: Each provincial reference panel included 30 to 36 members of the public who were randomly selected to represent the demographic characteristics of that province. Panels were held in Nova Scotia, Quebec, Ontario, Manitoba, and British Columbia. METHODS: OurCare panelists spent up to 40 hours learning about primary care from experts in each province and deliberating to reach consensus on values, issues, and recommendations. Provincial advisory committees were composed of clinician leaders, policy-makers, and researchers. In each province, OurCare panelists collectively developed a report summarizing the results of their deliberations. REPORT: Panels in all 5 provinces identified 3 major challenges affecting primary care: a growing health workforce crisis, inequitable access to care, and fragmented services. Participants emphasized that everyone in Canada should have timely, equitable access to primary care, and called for a system that is prevention-focused, inclusive, patient-centred, and accountable. In all provinces, panelists recommended expanding team-based care, improving health professional retention and recruitment, ensuring patient access to health records, addressing the social determinants of health, and educating and empowering patients. CONCLUSION: Results from the reference panels provide actionable direction for health system leaders, policy-makers, family physicians, and others engaged in health system improvement.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.026 | 0.005 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".