Queering autism: Heteronormative barriers to autism identification
Bibliographic record
Abstract
Autistic people are everywhere and not limited by any intersection including race, religion, country or culture. Many of us experience social oppression and disadvantage. In this autoethnography, I explore some of my experiences navigating being “different”, even in today’s culture. This analysis highlights key areas where culture can have a negative impact on autistic people. From a transfeminist disability studies framework, utilizing queer theory and the neurodiversity paradigm, I explore the positive impacts of queering autism within my own life. Through personal accounts of queering, I highlight how some heteronormative barriers can be reduced in one’s personal life, with the potential also to be applied more broadly within culture. Implications of queering autism broadly include an application within the medical and psychological fields and government autism program changes. Utilizing autoethnographic accounts and stories from within my community, I discuss the barriers to autism identification among those with numerous identities that do not align with stereotypical white cis male-centred autism concepts within culture that have also had impacted me throughout my lifespan. The stories told advocate for inclusive research and increased funding to share the stories of marginalized voices, policy changes and community education initiatives. I conclude with the importance of queering autism to increase access to autism self-identity, particularly among autistic people who are not cisgender males.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".