Diversity in Orthopaedic Surgery: International Perspectives
Bibliographic record
Abstract
Orthopaedic surgery in the United States is one of the few medical specialties that has consistently lacked diversity in its training programs and workforce for decades, despite increasing awareness of this issue. Is this the case in other English-language speaking countries? Are there inherent national differences, or does orthopaedics as a profession dictate the diversity landscape around the globe? The Carousel group includes the presidents of the major English-language-speaking orthopaedic organizations around the globe—Australia, Canada, New Zealand, South Africa, the United Kingdom, and the United States. Established in 1952, members of this group attend each other’s annual scientific meetings during the year of their presidency, learning about our profession in each country and building international relationships. In this article, 13 Carousel presidents from different countries explore diversity in orthopaedics in their training programs and the workforce, with an assessment of the current state and ideas for improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".