National survey of Canadian residents and program directors regarding parental leave during residency
Bibliographic record
Abstract
Background: Despite the advantages of having a child as a medical resident, the transition back to residency after parental leave can be challenging. This study is the first to investigate this issue using a nation-wide Canadian sample of both residents and program directors. Method: A questionnaire was developed and made available online. Respondents included 437 female residents, 33 male residents, and 172 residency program directors. The mean length of parental leave was nine months for female residents and six weeks for male residents. Almost all female residents (97.5%) breastfed with an average duration of 12 months. The top challenges reported by residents were feeling guilty for being away from their family, long and unpredictable work hours, sleep deprivation, and finding time to study. When female residents and program directors were matched to both school and program (N = 99 pairs), there was no difference in the total number of challenges reported, but program directors reported offering significantly more accommodations than female residents reported being offered, t(196) = 13.06, p < .001. Results: Our data indicate there is a need for better communication between resident parents and program directors, as well as clear program-specific parental leave policies, particularly for supporting breastfeeding mothers as they return to work.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".