The double-edged scalpel: Experiences and perceptions of pregnancy and parenthood during Canadian surgical residency training
Bibliographic record
Abstract
INTRODUCTION: Only 34% of Canadian surgeons in 2022 were female. The protracted length of surgical residency training, concerns regarding infertility, and increased rates of obstetrical complications have been shown to contribute to the disproportionate lack of females in surgical specialties. METHODS: A novel online survey was sent to all surgical residents in Canada. Respondents were asked about perceptions of pregnancy and parenthood during surgical training, and parents were asked about parental leave, accommodations they received, and pregnancy complications. Chi squared tests were used to compare opinions of male and female residents. RESULTS: A total of 272/2,419 (11.2%) responses were obtained, with a high response from females (61.8%) and orthopaedic residents (29.0%). There were 56 women reporting 76 pregnancy events during training, 62.5% of which had complications. Notably, 27.3% of men and 86.7% of women 'agreed' or 'strongly agreed' that surgeons have higher pregnancy complication rates than the general population (p<0.001). Men were much less likely to believe that pregnant residents should be offered modified duties (74.2% of men, 90.0% of women, p = 0.003). Women were much more likely to experience significant stigma or bias due to their status as a parent (43% of women, 0% of men, p<0.001). Women reported negative comments from others at a higher rate (58.5% of women, 40.7% of men, p = 0.013). Women believe there is negative stigma attached to being pregnant during training (62.7% of women, 42.7% of men, p = 0.01). The limitations of our study include a small sample size and response bias. CONCLUSION: Challenges and negative perceptions exist around pregnancy and parenthood in surgical residency, which disproportionately affect women trainees.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".