The Misuse of Gender Dysphoria: Toward Greater Conceptual Clarity in Transgender Health
Bibliographic record
Abstract
The notion of gender dysphoria is central to transgender health care but is inconsistently used in the clinical literature. Clinicians who work in transgender health must understand the difference between the diagnosis of Gender Dysphoria as defined and described in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders and the notion of this term as used to assess eligibility for transition-related interventions such as hormone-replacement therapy and surgery. Unnecessary diagnoses due to the belief that a diagnosis is clinically required to access transition-related care can contribute to stigma and discrimination toward trans individuals.
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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 | 0.052 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.085 |
| Scholarly communication | 0.015 | 0.022 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.001 | 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".