Proposed Changes to Diagnoses Related to Gender Identity in the<i>DSM</i>: A World Professional Association for Transgender Health Consensus Paper Regarding the Potential Impact on Access to Health Care for Transgender Persons
Bibliographic record
Abstract
The World Professional Association for Transgender Health (WPATH) has prepared a consensus statement to inform the Diagnostic and Statistical Manual (DSM) 5th Edition Work Group on Sexual and Gender Identity Disorder as it redefines the transgender experience. As part of that initiative, the authors of this article (a designated WPATH work group) looked at options for changing (or not changing) the DSM 5 diagnoses related to gender identity, taking into consideration how each of those options might affect access to care for transgender persons. Drawing on a thorough review of the literature, the WPATH work group undertook to describe the current and possible future states of access to health care; “access” defined according to established human rights measures, the “transgender experience” defined according to current DSM and International Classification of Diseases (ICD) codes. The role of various parties that influence access was considered, including transgender persons, care providers, policy writers, and decision makers in government and industry. A change to the DSM 5 that supports a normative transgender identity with distressed states is recommended in the context of a continuing dialogue between stakeholders.
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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 | 0.072 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".