Inappropriate Questions Asked of Female Orthopaedic Surgery Applicants From 1971 to 2015: A Cross-sectional Study
Bibliographic record
Abstract
INTRODUCTION: The Civil Rights Act prohibits employers from making employment decisions based on sex, race, color, religion, or national origin. Questions regarding these topics during a residency interview are therefore prohibited. METHODS: A questionnaire was sent to all female orthopaedic surgeons who had an e-mail address in the American Academy of Orthopaedic Surgeons directory. Participants were asked to describe what, if any, inappropriate questions they were asked during interviews. RESULTS: Four hundred eighty-eight of 997 invited female orthopaedic surgeons completed the questionnaire (48.9%). Their residency interviews took place from 1971 to 2015. Overall, 61.7% of participants were asked an inappropriate question during an interview. This proportion neither increased nor decreased from 1971 to 2015 (P = 0.315). The most common themes of questions included "raising children during residency" (37.9%), "marital status" (32.4%), and "pregnancy during residency" (29.7%). Of those who were asked an inappropriate question, only 1.4% reported the inappropriate question to authorities. DISCUSSION: The present study suggests that over half of female applicants have been asked inappropriate questions at orthopaedic surgery residency interviews, and that there has been no improvement in that percentage over nearly five decades. It is the responsibility those interviewing to be aware of this issue and to be in compliance with national guidelines. LEVEL OF EVIDENCE: Level IV.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".