Transgender Youth Health and Joy: A Model of Evidence-Based School District Policy Change to Support Transgender and Nonbinary Youth Health
Bibliographic record
Abstract
There are 1000 antitransgender bills across the United States, more than one quarter of which target educational settings. School districts are an increasingly critical policy domain through which transgender and nonbinary youth health is harmed and can be protected. Trans-led resistance, including activism and advocacy, has been found to lead to improved health. This case study describes one California school district’s policy advocacy process as a model for building transgender youth health through a participatory process that, in itself, has supported transgender joy. ( Am J Public Health. Published online ahead of print November 13, 2025:e1–e4. https://doi.org/10.2105/AJPH.2025.308264 )
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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 | 0.063 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.010 | 0.010 |
| 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".