Experiences of Canadian Female Orthopaedic Surgeons in the Workplace
Bibliographic record
Abstract
BACKGROUND: Only 13.6% of orthopaedic surgeons in Canada are women, even though there is nothing inherent to the practice of orthopaedic surgery that favors men over women. Clearly, there is a need to identify, define, and measure the barriers faced by women in orthopaedic surgery. METHODS: An electronic survey was distributed to 330 female-identifying Canadian orthopaedic surgeons and trainees and included the validated Gender Bias Scale (GBS) and questions about career burnout. The barriers for women in Canadian orthopaedics were identified using the GBS. The relationships between the GBS and burnout were investigated. Open-text questions explored the barriers perceived by female orthopaedic surgeons. RESULTS: The survey was completed by 220 female orthopaedic surgeons and trainees (66.7%). Five barriers to gender equity were identified from the GBS: Constrained Communication, Unequal Standards, Male Culture, Lack of Mentoring, and Workplace Harassment. Career burnout correlated with the GBS domains of Male Privilege (r = 0.215; p < 0.01), Disproportionate Constraints (r = 0.152; p < 0.05), and Devaluation (r = 0.166; p < 0.05). Five main themes emerged from the open-text responses, of which 4 linked closely to the barriers identified in the GBS. Work-life integration was also identified qualitatively as a theme, most notably the difficulty of balancing disproportionate parental and childcare responsibilities alongside career aspirations. CONCLUSIONS: In this study, 5 barriers to workplace equity for Canadian female orthopaedic surgeons were identified using the validated GBS and substantiated with qualitative assessment using a mixed-methods approach. Awareness of these barriers is a necessary step toward dismantling them and changing the prevailing culture to be fair and equitable for all. CLINICAL RELEVANCE: A just and equitable orthopaedic profession is imperative to have healthy and thriving surgeons who are able to provide optimal patient care.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".