Analysis of Obstetrics and Gynecology Residency Program Website Contents in the United States of America
Bibliographic record
Abstract
Background Obstetrics and gynecology (OB/GYN) residency program websites are essential resources for applicants when selecting a residency program. Assessing these websites against a 58-point criterion can provide program administrators with actionable insights to enhance their content and make them more informative for applicants. Objective This study aims to evaluate the comprehensiveness of content on American OB/GYN residency program websites. Methods We reviewed American OB/GYN residency program websites listed on the Fellowship and Residency Electronic Interactive Database (FRIEDA). A 58-point criterion was developed based on the Accreditation Council for Graduate Medical Education (ACGME) common program requirements and prior studies. The criteria included seven categories. Programs without a webpage, military-based programs, and non-US-based programs were excluded. Results A total of 272 program websites met the inclusion criteria. On average, websites contained only 28 of the 58 study criteria (48.6%). The most commonly included information was the residency manual (59.1%), while details about didactics and program structure were the least commonly included (40.7%). Conclusion The majority of American OB/GYN residency program websites lack comprehensive information for applicants. Residency programs should consider incorporating key details such as application information, introduction to the program, residency manual, didactics and program description, research, current resident information, and graduate/post-residency placement.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".