International surgery: the development of postgraduate surgical training in Guyana.
Bibliographic record
Abstract
BACKGROUND: Like many developing countries, Guyana has a severe shortage of surgeons. Rather than rely on overseas training, Guyana developed its own Diploma in Surgery and asked for assistance from the Canadian Association of General Surgeons (CAGS). This paper reviews the initial results of Guyana's first postgraduate training program. METHODS: We assisted with program prerequisites, including needs assessment, proposed curriculum, University of Guyana and Ministry of Health approval, external partnership and funding. We determined the outputs and outcomes of the program after 2 years, and we evaluated the impact of the program through a quantitative/qualitative questionnaire administered to all program participants. RESULTS: Five residents successfully completed the 2-year program and are working in regional hospitals. Another 9 residents are in the training program. Twenty-four modules or short courses have been facilitated, alternating Guyanese with visiting Canadian surgical faculty members coordinated through CAGS. A postgraduate structure, including an Institute for Health Sciences Education and Surgical Postgraduate Education Committee, has been developed at the Georgetown Public Hospital Corporation (GPHC). An examination structure similar to Canada's has been established. Hospital staff morale is greater, surgical care is more standardized and academic opportunities have been enhanced at GPHC. Four regional hospitals have welcomed the new graduates, and surgical services have already improved. Canadian surgeons have a greater understanding of and commitment to surgical development in low-income countries. CONCLUSION: Guyana has proven that, with visiting faculty assistance, it can mount its own postgraduate training suitable to national needs and will provide a career path to encourage its own doctors to remain and serve their country.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".