Variation in training requirements within general surgery: comparison of 23 countries
Bibliographic record
Abstract
Background: Many differences exist in postgraduate surgical training programmes worldwide. The aim of this study was to provide an overview of the training requirements in general surgery across 23 different countries. Methods: A collaborator affiliated with each country collected data from the country's official training body website, where possible. The information collected included: management, teaching, academic and operative competencies, mandatory courses, years of postgraduate training (inclusive of intern years), working-hours regulations, selection process into training and formal examination. Results: Countries included were Australia, Belgium, Canada, Colombia, Denmark, Germany, Greece, Guatemala, India, Ireland, Italy, Kuwait, the Netherlands, New Zealand, Russia, Saudi Arabia, South Africa, South Korea, Sweden, Switzerland, UK, USA and Zambia. Frameworks for defining the outcomes of surgical training have been defined nationally in some countries, with some similarities to those in the UK and Ireland. However, some training programmes remain heterogeneous with regional variation, including those in many European countries. Some countries outline minimum operative case requirement (range 60-1600), mandatory courses, or operative, academic or management competencies. The length of postgraduate training ranges from 4 to 10 years. The maximum hours worked per week ranges from 38 to 88 h, but with no limit in some countries. Conclusion: Countries have specific and often differing requirements of their medical profession. Equivalence in training is granted on political agreements, not healthcare need or competencies acquired during training.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".