383 An International Comparison of Competency-Based Orthopaedic Curricula and Minimum Operative Numbers
Bibliographic record
Abstract
Abstract Introduction The requirements for completion of surgical training can vary across different countries. This review aims to assess key differences among orthopaedic curricula in selected high-income countries, focusing on their criteria for assessing technical competence for completion of training. Method Current orthopaedic training curricula in the UK, USA, Canada, Australia, and Germany were reviewed. Data extracted included training duration, minimum or desirable operative experience requirements, methods, and timing of in-training assessments. Results The overall training duration ranged between 9-10 years in the UK and Australia, compared to 5-6 years in all other countries. While operative logbook was an essential component of formative and end-of-training reviews in all countries, minimum indicative numbers in index operations were a requirement only in the UK (minimum total required; 1800, index operations; 365) and USA (minimum total required; 1000, index operations; 455). On average, USA residents performed 1,700 procedures compared to German residents performing 730 procedures before completion of training. Conclusions There is a lack of robust data describing the operative experiences of orthopaedic trainees outside of the UK and USA. Contrary to common perception, surgeons exiting training and entering independent practice in the above countries are not trained to the same minimum standard.
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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 | 0.012 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".