LGBTQ+ realities in the biological sciences
Bibliographic record
Abstract
ABSTRACT While scientific environments have been described as unwelcoming to the LGBTQ+ community, and fields such as physics have systematically documented these challenges, the climate in biology workplaces has not been assessed. We conducted the largest survey to date of LGBTQ+ biologists to examine how their sense of belonging and perception of climate in the biology workplace and professional societies compare to that of their straight and cis peers. We surveyed 1419 biologists across five professional societies, with 486 identifying as LGBTQ+. Trans and gender non-conforming (TGNC) biologists reported lower belonging and morale within the workplace, professional societies, and the biology community compared to cis, straight biologists. They also reported being less comfortable with the climate of various professional biology environments. While LGBTQ+ biologists report that their workplaces are moderately inclusive, over 20% of all LGBTQ+ biologists and nearly 40% of TGNC biologists experience exclusionary behavior at work. This landmark survey provides the first comprehensive analysis of the LGBTQ+ climate in biology, revealing specific challenges faced by TGNC scientists and identifying interventions to enhance inclusivity for scientists. Significance Statement This landmark study includes the largest known sample of LGBTQ+ biologists and offers the first comprehensive description of the LGBTQ+ climate in biology, differentiating between the experiences of cisgender lesbian, gay, bisexual, and queer (LGBQ) biologists and transgender and gender non-conforming (TGNC) biologists. The study found that compared to non-LGBTQ+ biologists, TGNC participants report lower belonging, morale and comfort with the climate across biology workplaces, professional societies, and the biology community. While on average LGBTQ+ participants reported that their workplaces are moderately inclusive, over 20% of all LGBTQ+ biologists and nearly 40% of TGNC biologists report experiencing exclusionary behaviors at work. The study offers immediate implications for institutional policies and professional development in the biological sciences.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".