“I had this fear that as an autistic person, they would take me less seriously”: Trans autistic experiences of epistemic (in)justice in gender-affirming care
Bibliographic record
Abstract
Background A disproportionate number of transgender and nonbinary people are autistic, and research suggests that trans autistic people experience significant barriers and challenges to accessing gender-affirming care. Much of the existing research in this area focuses on determining why trans people are more likely to be autistic, and less research has attended to trans autistic people’s lived experiences of accessing gender-affirming care.Methods To better understand these barriers and their impacts, I conducted qualitative interviews with 12 trans autistic people who had recently accessed gender-affirming medical care in the province of Ontario, Canada. Interviews were analyzed using reflexive thematic analysis.Results Participants reported being frequently not believed, listened to, or taken seriously by healthcare providers, which I conceptualize as instances of epistemic injustice. I identify how medical discourses, ideologies, and clinical guidelines create conditions for gender-affirming care in which trans autistic people experience pervasive epistemic injustice. For example, participants felt pressure to conform to a transnormative and neuronormative narrative in order to be taken seriously by gender-affirming care providers. Some providers misinterpreted autistic communication styles and unfairly discredited their client’s knowledge, eroding their trust in health care. While participants used creative self-advocacy strategies to access care, some providers felt threatened by this challenge to their epistemic power and medical authority. Conversely, participants also had positive experiences of epistemic justice when providers took their knowledge and lived experience seriously.Conclusion I argue that gender-affirming care providers must practice epistemic humility by listening deeply and acknowledging the limits of their knowledge to deliver patient-centered care for trans autistic people. Systemic changes to the healthcare system and disrupting transnormativity and neuronormativity are necessary to improve trans autistic people’s experiences of gender-affirming care and enable epistemic justice.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.039 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.011 |
| 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".