Family Planning Among Canadian Plastic Surgeons and Trainees
Bibliographic record
Abstract
Introduction: Despite increasing advocacy for family leave policies, few studies have described the current landscape and attitudes around family planning in Canadian plastic surgery. The purpose of this study was to survey Canadian plastic surgeons and trainees to examine their experience with family planning, parental leave, and breastfeeding. Methods: An anonymized survey was distributed to all members of the Canadian Society of Plastic Surgeons and all Canadian Plastic Surgery residents through their program administrators. Survey responses were recorded and analyzed through a customized REDCap™ database. Results were reported using descriptive statistics. Results: A total of 87 plastic surgeons and trainees completed the surgery. We found 72.3% of respondents had children; 67.8% felt their colleagues were supportive of parental leave; 45.6% felt that financial concerns affected their decision to take parental leave; 61.6% felt that their career did not influence the number of children they chose to have; 21.0% accessed fertility services and 9.8% used assisted-reproductive technologies; 80% of respondents who breastfeed felt they did not have enough time to pump at work, however, 79% did not experience any discrimination or criticism for pumping at work. Conclusion: Canadian plastic surgeons most often have children after completing training and choose to take shorter parental leaves as their careers progress. Parental leave and breastfeeding practices in the workplace are reported to have increased support from colleagues compared to previous literature. However, Canadian plastic surgeons continue to struggle with infertility and seek fertility services at rates higher than the general population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".