Experiences of LGBTQ+ Plastic Surgeons in the US and Canada
Bibliographic record
Abstract
Background : The LGBTQ+ community faces discrimination within the workplace, with growing evidence emerging about the mistreatment of LGBTQ+ surgeon trainees. The purpose of this study was to better understand the experiences of LGBTQ+ surgeons in plastic and reconstructive surgery (PRS). Methods: A web-based survey was made available to all plastic surgeons who identified as LGBTQ+ across the US and Canada from October 2021 to November 2022. The questionnaire used validated tools assessing “outness” and microaggressions, as well as rates of censorship of speech and/or mannerisms and experiences of discrimination. Outcomes were measured as frequencies and analyzed as a function of location (US vs Canada), gender identity (transgender and gender-diverse (TGD) versus cisgender), and level of training (attending vs in-training). Qualitative responses were also recorded. Results: A total of 43 self-identified LGBTQ+ individuals engaged with the survey, 38 of which completed it (88%). Nearly all (96.8%) reported experiencing heteronormative microaggressions, 36.7% reported discrimination from plastic surgery attendings, and 73.3% censor themselves around Plastic Surgery attendings. TGD respondents were more likely to have experienced discrimination than cisgender respondents ( P < .01). One-third (33%) of respondents indicated that they hesitate to be out at their institution for fear of bias and/or discrimination. Conclusion: LGBTQ+ plastic and reconstructive surgeons reported a significant amount of microaggressions, self-censorship, and discrimination while at work, and these experiences varied as a function of level of training and gender identity. PRS should strive to eliminate these mistreatments, educate its workforce, and address LGBTQ+ underrepresentation within the field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".