Trends in Bullying Victimization and Social Unsafety for Sexually and Gender Diverse Students
Bibliographic record
Abstract
Research has documented trends in bullying victimization for sexually diverse adolescents in the US, but trends regarding school social unsafety are understudied and there is a dearth of research examining these trends for gender diverse adolescents. This study aimed to identify disparities in bullying victimization and feelings of social unsafety in schools for sexually and gender diverse adolescents. Data stem from the 2014 (N = 15,800; M age = 14.17, SD = 1.50), 2016 (N = 22,310; M age = 14.17, SD = 1.49), and 2018 (N = 10,493; M age = 14.02, SD = 1.52) survey cycles of the Social Safety Monitor, a Dutch cross-sectional school-based study. Findings indicate that sexual orientation disparities remained relatively small, but stable over time, while gender diverse adolescents remained more likely to be victimized and feel unsafe in school, with larger disparities overall. Monitoring these trends is highly relevant, especially considering recent negative developments regarding societal acceptance of sexual and gender diversity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".