“The Damage Happens … You Just Try Not to Dwell on It”: Experiences of Discrimination by Gender and Sexual Minority Veterinary Professionals and Students in the US and the UK
Bibliographic record
Abstract
Data collected in a 2016 survey of veterinary students and professionals from the United States and the United Kingdom who identified as lesbian, gay, bisexual, transgender, queer, questioning, or asexual (LGBTQ+) indicated that 34.5% (152/440) had experienced difficulties related to their sexual orientation or gender identity at school or work. This study’s objective was to examine narrative responses collected in the 2016 survey and utilize content analysis to explore the research questions: What are the concerns of the LGBTQ+ veterinary population, and how do they attempt to resolve difficulties at work and school? To address these questions, we developed two taxonomies that cataloged (a) the difficulties reported by veterinary professionals and students in the 2016 survey sample and (b) the outcomes of their attempts to resolve these difficulties. The themes related to difficulties that occurred most frequently were exposure to homophobic or transphobic language ( n = 69; 45.4%), outness/staying in the closet (45, 29.6%), and negative emotional outcomes (32, 21.2%). The most common themes that described the outcomes of their attempts to resolve those difficulties were unresolved ( n = 41, 27.0%), changed jobs or graduated (22, 14.5%), and found self-acceptance of acceptance from others (21, 13.8%). Our findings can inform the efforts of schools and colleges of veterinary medicine, professional organizations, and workplaces in targeting improvements to support LGBTQ+ students and professionals and the development of measures tailored to this population.
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 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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".