Bibliographic record
Abstract
PURPOSE: It is estimated that by 2010 30% of U.S. physicians will be women. Pregnancy during residency can and does happen in all programs, and continues to provide problems for many. The author reviews the issues surrounding pregnancy during residency by evaluating published commentaries and research reports. METHOD: A literature search was conducted using Medline (January 1984-October 2001). Published articles were categorized as research or commentary. Research reports were sorted by content and summarized under three headings: mother and infant health, sources of stress and support for the pregnant resident, and reactions of colleagues to the pregnant resident. RESULTS: A total of 27 research reports were located; two additional reports published before 1984 were added because they complemented included studies. The majority of the studies in this review used retrospective self-report questionnaires, mostly completed by female residents and physicians. All reports suggested an increased risk of complications, especially adverse late-pregnancy events, for pregnant physicians. Pregnant residents found the physical demands of residency and lack of support from fellow residents and their departments most stressful. Anger and resentment toward the pregnant resident were common among not-pregnant residents, feelings particularly associated with expectations of increased workload. Individual maternity/parental leave policies were inconsistent. Policy development is discussed. CONCLUSIONS: The studies in this review supported planning for residents' pregnancies, and the author advocates clear maternity/parental leave policies. The author comments on the use of existing data to make common sense changes and on the need for further studies to help clarify the issues and evaluate program changes.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".