Pregnancy and parental leave among plastic surgery residents in Canada: a nationwide survey of attitudes and experiences
Bibliographic record
Abstract
Pregnancy and parental leave among plastic surgery residents in Canada: a nationwide survey of attitudes and experiences O n average, following the completion of a surgical residency, exiting trainees in Canada are 33.2 years of age. 1 The average age at which mothers in Canada had their first child was 29.2 years in 2016. 2 Therefore, residents who hope to start a family may consider pregnancy dur ing their training. However, surgical residents are in an undesirable position to start a family because of their long work hours, the physically demanding nature of their work, specific occupational hazards and less flexibility in resi dency rotation scheduling. 3 A survey of members and candidates of the Amer ican Society of Plastic Surgeons found that 72.6% of women and 39.2% of men delayed having children because of the demands of training. 4 As there is an increased risk of both maternal and fetal complications related to deferred childbirth, especially after age 35, many plastic surgery graduates may find themselves conflicted between the demands of a professional career and par enting priorities. 5 With only 26 new trainees starting plastic surgery residencies each year in Canada, it can be challenging for small surgical programs like plastic surgery to accommodate parental leave. Starting a family during residency can be compli cated and situationally dependent, and it is important to understand the impact of the environment on this life event by investigating the experiences of resi dents and recent graduates across Canada. This study aimed to report the experiences, attitudes and perceived support of Canadian plastic surgery resi dents and surgeons with respect to pregnancy and parenting during training.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".