Are Canadian orthopaedic surgeons and American orthopaedic surgeons on par? A Canadian practice survey of orthopaedic traumatologists
Bibliographic record
Abstract
Objectives: The purpose of this study was to obtain information on Canadian orthopaedic trauma surgeon practices and salary demographics. It was hypothesized that most of the practicing surgeons recognize specific practice aspects (compensation, call schedule, operating room availability, and provided support staff) as key factors in employment opportunity evaluation. Design: Cross-sectional survey study. Setting: Orthopaedic Trauma Association (OTA) practice surveys. Participants: All active Canadian members of the OTA were eligible to participate. Main Outcome Measurement: A 50-question survey was sent through email to OTA members assessing physician, practice, and compensation metrics of Canadian orthopaedic traumatologists. Results: Fifty-two of 113 Canadian OTA members participated giving a response rate of 46%. All surgeons worked in an academic practice, either for a university (83%) or community hospital (17%). Only 2% of surgeons have changed jobs in the last 5 years, and over 73% of surgeons maintain the same place of employment during their careers. Most had an available dedicated orthopaedic trauma operating room (73%). The majority indicated having residents (71%) and fellows (63%) as support staff. Many reported completing 300-500 cases per year (42%), which decreased during COVID-19 for 50% of surgeons. The most common reported compensation was between $400,000 and $600,000 US dollars (25%) with many working 4-6 call shifts a month (48%) and 51-70 hours a week (48%). Conclusion: This study demonstrated the varying practice and physician economic variables currently in Canada. The identification and continued surveillance of these employment variables will allow for transparency in job market evaluation by applicants. Level of Evidence: Level V.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".