Family medicine around the world: overview by region: The Besrour Papers: a series on the state of family medicine in the world.
Bibliographic record
Abstract
OBJECTIVE: To demonstrate how family medicine has been recognized and integrated into primary health care systems in contrasting contexts around the world and to provide an overview of how family physicians are trained and certified. COMPOSITION OF THE COMMITTEE: Since 2012, the College of Family Physicians of Canada has hosted the Besrour Conferences to reflect on its role in advancing the discipline of family medicine globally. The Besrour Papers Working Group, which was struck at the 2013 conference, was tasked with developing a series of papers to highlight the key issues, lessons learned, and outcomes emerging from the various activities of the Besrour collaboration. The working group comprised members of various academic departments of family medicine in Canada and abroad who attended the conferences. METHODS: An initial search was conducted in PubMed using a family medicine hedge of MeSH terms, text words, and family medicine journals, combined with text words and terms representing low- and middle-income countries and the concept of family medicine training programs. A second search was completed using only family medicine terms in the CAB Direct and World Bank databases. Subsequent PubMed searches were conducted to identify articles about specific conditions or services based on suggestions from the authors of the articles selected from the second search. Additional articles were identified through reference lists of key articles and through Google searches. We then attempted to verify and augment the information through colleagues and partners. REPORT: The scope of family medicine and the nature of family medicine training vary considerably worldwide. Challenges include limited capacity, incomplete understanding of roles, and variability of standards and recognition. Opportunities for advancement might include technology, collaboration, changes in pedagogy, flexible training methods, and system-wide support.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.026 | 0.026 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".