Nurturing a culture of curiosity in family medicine and primary care
Bibliographic record
Abstract
OBJECTIVE: To describe Blueprint 2 (2018-2023), the 5-year strategic plan launched in 2018 by the Section of Researchers (SOR), as well as its guiding principles and the process used to develop it. COMPOSITION OF THE COMMITTEE: Blueprint 2 was co-created by many stakeholders from across Canada and led by the SOR Council (SORC). The process started with an external, commissioned program evaluation in 2017 of the effect of the first SOR Blueprint (2012-2017). The findings and recommendations arising from the evaluation were presented in a day-long facilitated invitational retreat, hosted by the SORC in September 2017 and involving 40 key stakeholders. METHODS: Blueprint 2 was created using a multi-pronged, participatory, and iterative process to ensure broad input and alignment with current and future opportunities and priorities. REPORT: Blueprint 2 incorporates 4 strategic priority areas, each supported by objectives and actions. The strategic priority areas are membership, capacity building, advocacy, and partnerships. This updated Blueprint provides a useful, membership-driven strategic plan specifically for the SOR. The implementation of its objectives will promote research and quality improvement and contribute to building a culture of curiosity. Blueprint 2 emphasizes research and quality improvement that emanate from the realities of everyday practice and are rooted in everyday work. At its core are patient- and community-oriented approaches; it also contributes to achieving the Quadruple Aim. These outcomes will further the integration of the scholar role into daily practice for family physicians and primary care clinicians and teams. CONCLUSION: The ability of family physicians to identify, study, and cite their own evidence is essential to establishing the value and effect of primary care, including family medicine, in relation to Canadians' health and the Canadian health care system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".