Proposal to set up a College of Family Medicine in East, Central and Southern Africa
Bibliographic record
Abstract
Family Medicine training in Africa is constrained by limited postgraduate educational resources and opportunities. Specialist training programmes in surgery, anaesthetics, internal medicine, paediatrics and others have developed a range of trainers and assessors through colleges across East, Central and Southern Africa (ECSA). Each college has a single curriculum with standardised training and assessment in designated institutions, which run alongside and in collaboration with the Master's in Medicine programmes in universities. Partnerships between colleges in Britain, Ireland and Canada and national specialist associations have led to joint training-of-trainer courses, e-learning platforms, improved regional coordination, better educational networking and research opportunities through regional conferences and joint publications. We propose the establishment of a regional college for specialist training of family physicians, similar to other specialist colleges in ECSA. Partnerships with family medicine programmes in South Africa, Canada and Australia, with support from international institutions such as the Primary Care and Family Medicine Network for Sub-Saharan Africa (PRIMAFAMED) and the World Organisation of Family Doctors (WONCA Africa), would be essential for its success. Improved health outcomes have been demonstrated with strong primary care systems and related to the number of family physicians in communities. A single regional college would make better use of resources available for training, assessment and accreditation and strengthen international and regional partnerships. Family medicine training in Africa could benefit from the experience of specialist colleges in the ECSA region to accelerate training of a critical mass of family physicians. This will raise the profile of family medicine in Africa and contribute to improved quality of primary care and clinical services in district hospitals.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.044 | 0.010 |
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".