North–South surgical training partnerships: a systematic review
Bibliographic record
Abstract
Background: Fostering the success of surgical trainees from low- and middle-income countries (LMICs) plausibly addresses the existing workforce deficit in a sustainable manner, but it is unclear whether and how these trainees are targeted as strategic learners for educational exchanges. The purpose of this review was to assess the quality and outcomes of existing literature on exchanges of surgical trainees between high-income countries (HICs) and LMICs. Methods: We conducted a systematic review of reported instances of surgical training exchanges between HICs and LMICs. After database searching, 2 independent reviewers evaluated titles, abstracts and manuscripts. Selected studies were critically appraised with the use the Critical Assessment Skills Programme Qualitative Checklist and analyzed for trainee level, institutions, countries and subspecialties, as well as reported outcomes of the exchange. Results: Twenty-eight reports met the inclusion criteria and were analyzed. Most publications (18 [64%]) detailed North-to-South exchanges; 1 exchange was bidirectional. General surgery was the most common discipline identified, with 9 other subspecialties described involving learners at all phases of training. Reports were generally of good quality, although outcomes were reported variably, and most authors failed to acknowledge the ethical implications of their study. Conclusion: The articles identified described a variety of surgical exchanges across disciplines, learner types and host/home countries. Few of the exchanges prioritized the learning of surgical trainees from LMICs. There is an increasing need to formalize these exchanges via clear goals and objectives, as well as to prioritize the proper matching of educational goals with local clinical needs. Level of evidence: V - Evidence from systematic reviews of descriptive and qualitative studies.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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".