Parental Leave Policies in Canadian Residency Education
Bibliographic record
Abstract
BACKGROUND: In recent decades, the gender makeup of Canadian medical residents has approached parity. As residency training years coincide closely with childbearing years and paid parental leave is associated with numerous benefits for both parents and children, it is important for there to be clarity about parental leave benefits. OBJECTIVES: We aimed to conduct a comprehensive review of maternity and parental leave policies in all residency education programs in Canada, to highlight gaps that might be improved or areas in which Canadian programs excel. METHODS: We searched websites of the 8 provincial housestaff organizations (PHOs) for information regarding pregnancy workload accommodations, maternity leave, and parental leave policies in each province in effect as of January 2020. We summarized the policies and analyzed their readability using the Flesch Reading Ease. RESULTS: All Canadian PHOs provide specific accommodations around maternity and parental leave for medical residents. All organizations offer at least 35 weeks of total leave, while only 3 PHOs offer extended leave of about 63 weeks, in line with federal regulations. All but 2 PHOs offer supplemental income to their residents, although not for the full duration of offered leave. All PHOs offer workplace accommodations for pregnant residents in their second and/or third trimester. CONCLUSIONS: Although all provinces had some form of leave, significant variability was found in the accommodations, duration of leave, and financial benefits provided to medical residents on maternity and parental leave across Canada. There is a lack of clarity in policy documents, which may be a barrier to optimal uptake.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".