Affirming Everyone in the Rainbow: Is Gender-Affirming Healthcare “Gay Conversion Therapy?”
Bibliographic record
Abstract
Many young people today embrace gender-diverse identities, with adolescents and young adults comprising the largest and fastest-growing demographic of gender-affirming healthcare seekers. Simultaneously, gender-affirming healthcare for this demographic has been debated, and restrictions have been introduced in many jurisdictions. Within this politically charged climate, some journalists, cultural commentators, gender clinicians and politicians have leveraged rhetorical claims that gender-affirming healthcare comprises a new form of "gay conversion therapy." In this commentary, we explore the extent to which empirical evidence supports or contradicts this discourse as a real phenomenon. While we conclude that gender-affirming healthcare is not gay conversion therapy, we also draw attention to opportunities to enrich gender-affirming healthcare by embracing the complexity of sexuality and gender.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.053 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.013 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".