<scp>LGBTQ</scp> Youth's Views on Gay‐Straight Alliances: Building Community, Providing Gateways, and Representing Safety and Support
Bibliographic record
Abstract
BACKGROUND: Gay-Straight Alliances (GSAs) are school-based clubs that can contribute to a healthy school climate for lesbian, gay, bisexual, transgender, and questioning (LGBTQ) youth. While positive associations between health behaviors and GSAs have been documented, less is known about how youth perceive GSAs. METHODS: A total of 58 LGBTQ youth (14-19 years old) mentioned GSAs during go-along interviews in 3 states/provinces in North America. These 446 comments about GSAs were thematically coded and organized using Atlas.ti software by a multidisciplinary research team. RESULTS: A total of 3 themes describe youth-perceived attributes of GSAs. First, youth identified GSAs as an opportunity to be members of a community, evidenced by their sense of emotional connection, support and belonging, opportunities for leadership, and fulfillment of needs. Second, GSAs served as a gateway to resources outside of the GSA, such as supportive adults and informal social locations. Third, GSAs represented safety. CONCLUSIONS: GSAs positively influence the physical, social, emotional, and academic well-being of LGBTQ young people and their allies. School administrators and staff are positioned to advocate for comprehensive GSAs. Study findings offer insights about the mechanisms by which GSAs benefit youth health and well-being.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".