Bibliographic record
Abstract
Abstract Lesbian, gay, bisexual, transgender, and queer (LGBTQ or LGBTQ+ if the latter context includes other identities) individuals tend to experience high levels of minority stress, which might increase their mental health challenges. Especially for LGBTQ individuals in low- and middle-income countries (LMICs), they might additionally experience inadequate access to physical and mental health services, limited financial support, low levels of education, and limited capacity of their governments to solve the societal oppression of this population, which can aggravate minority stress. Social support can buffer the negative effects of minority stress and allow someone to feel cared for, loved, esteemed, valued, and as belonging in their communities. This chapter presents a general overview of social support LGBTQ people may receive from their parents, siblings, school peers, teachers, intimate partners, and colleagues. We also describe the benefits of specific communities of LGBTQ-identifying people, including those who identify as a nonbinary gender, intersex, or asexual/aromantic; those with interests in BDSM, leather, or polyamory lifestyles; people living with HIV; LGBTQ youth and seniors; and virtual and religious communities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.090 | 0.015 |
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".