LGBTQ+ identity concealment and disclosure within the (heteronormative) health professions: “Do I? Do I not? And what are the potential consequences?”
Bibliographic record
Abstract
In the power-laden context of the health professions, disclosure of LGBTQ+ (or queer) identities carries particular risks, with disclosures to patients/clients seen as ‘unprofessional.’ Pervasive heterosexism and heteronormativity regulate professionals toward conformity, leaving them with ongoing strategic decision-making regarding identity concealment/disclosure. In this qualitative study with 13 health professionals (nurses, physicians, occupational therapists) from across Canada we used in-depth interviews to examine how they engaged with concealment/disclosure and impression management in heteronormative professional contexts. Most disclosed at least selectively with colleagues, but far more rarely with patient/clients, citing harm to therapeutic rapport and violation of professional boundaries. Navigating concealment/disclosure was exhausting and energy-consuming, with constant risk-benefit calculations on multiple levels. Culture change within the professions is critical to create work contexts in which LGBTQ + people can be fully themselves, in turn providing safer spaces for queer patients/clients.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.023 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".