Current Status of Family Medicine Faculty Development in Sub-Saharan Africa.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Reducing the shortage of primary care physicians in sub-Saharan Africa requires expansion of training programs in family medicine. Challenges remain in preparing, recruiting, and retaining faculty qualified to teach in these pioneering programs. Little is known about the unique faculty development needs of family medicine faculty within the sub-Saharan African context. The purpose of this study was to assess the current status and future needs for developing robust family medicine faculty in sub-Saharan Africa. The results are reported in two companion articles. METHODS: A cross-sectional study design was used to conduct a qualitative needs assessment comprising 37 in-depth, semi-structured interviews of individual faculty trainers from postgraduate family medicine training programs in eight sub-Saharan African countries. Data were analyzed according to qualitative description. RESULTS: While faculty development opportunities in sub-Saharan Africa were identified, current faculty note many barriers to faculty development and limited participation in available programs. Faculty value teaching competency, but institutional structures do not provide adequate support. CONCLUSIONS: Sub-Saharan African family physicians and postgraduate trainee physicians value good teachers and recognize that clinical training alone does not provide all of the skills needed by educators. The current status of limited resources of institutions and individuals constrain faculty development efforts. Where faculty development opportunities do exist, they are too infrequent or otherwise inaccessible to provide trainers the necessary skills to help them succeed as educators.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".