Parental Leave for Residents at Programs Affiliated With the Top 50 Medical Schools
Bibliographic record
Abstract
BACKGROUND: Of the top 15 medical schools with affiliated graduate medical education (GME) programs, 8 offer paid parental leave, with an average duration of 6.6 weeks. It is not known how other GME programs approach parental leave. OBJECTIVE: We searched for the parental leave policies for residents in programs affiliated with the top 50 medical schools. METHODS: in the research and primary care categories (totaling 59 schools), and identified the associated GME programs. For each school, we accessed its website and searched for "GME Policies and Procedures" to find language related to maternity, paternity, or parental leave, or the Family Medical Leave Act. If unavailable, we e-mailed the GME office to identify the policy. RESULTS: Of 59 schools, 25 (42%) described paid parental leave policies with an average of 5.1 weeks paid leave; 11 of those (44%) offer ≤ 4 weeks paid parental leave. Twenty-five of 59 (42%) programs did not have paid parental leave, but 13 of these specify that residents can use sick or vacation time to pay for part of their parental leave. Finally, 13 of 59 (22%) offered state mandated partial paid leave. One school did not have any description of parental leave. CONCLUSIONS: While paid parental leave for residents has been adopted by many of the GME programs affiliated with the top 50 medical schools, it is not yet a standard benefit offered to the majority of residents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".