Discrimination des minorités sexuelles et de genre au travail : quelles implications pour la santé mentale ?
Bibliographic record
Abstract
Despite legislative advances in terms of workplace equality for sexual and gender minorities (SGM), available data ascertains the persistence of workplace discrimination of lesbian, gay, bisexual, and especially of transgender/transsexual employees. This article, based on an extensive literature review, explores the relationship between different types of workplace discrimination experiences and their impacts on the mental health of SGM and of different sub-populations: men who have sex with men, non-heterosexual women, lesbian and gay parents, and trans people. Furthermore, the article explores certain individual and systemic protection and risk factors that have an impact on this relationship, such as coming-out at work and organisational support. Finally, the existing literature on workplace discrimination and mental health of sexual and gender minorities highlights the importance, in the current legal and social context, of intersectional approaches and of research on homo- and trans-negative microaggressions. The article ends with a discussion on the implications for practice, research, and workplace settings, as well as with several recommendations for these settings.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| 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".