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Record W4380569899 · doi:10.1089/aut.2023.0042

The Intersection of Autism and Transgender and Nonbinary Identities: Community and Academic Dialogue on Research and Advocacy

2023· article· en· W4380569899 on OpenAlexaff
F. Gratton, John F. Strang, Minneh Song, Kate Cooper, Aimilia Kallitsounaki, Meng‐Chuan Lai, Wenn Lawson, Anna I. R. van der Miesen, Harriette Wimms

Bibliographic record

VenueAutism in Adulthood · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsCentre for Addiction and Mental Health
FundersLiga Portuguesa Contra o Cancro
KeywordsTransgenderAutismPsychologyMinority stressDiversity (politics)Psychological resilienceGender diversityDevelopmental psychologySocial psychologySexual orientationSociologyPsychoanalysisSexual minority

Abstract

fetched live from OpenAlex

Many transgender people are autistic. Community expressions of the autism transgender intersection abound. Some commentators have questioned the proportional overrepresentation of autism among gender-diverse people, suggesting these individuals may not be truly autistic or truly transgender. However, increasing evidence challenges assertions that deny the authenticity of co-occurring autistic and transgender identities. Specifically, research by authors of this article indicates autistic transgender people show neurophenotypes generally consistent with cisgender autistic people and implicit gender phenotypes consistent with nonautistic transgender people. This article features a dialogue between eight leading experts in the field of intersectional autism and gender diversity, including clinicians, researchers, community advocates, and experts who are themselves autistic transgender. Key topics of discussion included: how research findings on autism and gender diversity inform respectful and supportive responses to autistic transgender people; the benefits and harms of increased societal attention toward the autism transgender intersection; and research and advocacy priorities. The expert panel concluded the following: (1) it is important to respect transgender autistic people's wellness and resilience, while also acknowledging the pathologization and stigmatization they face; (2) autistic gender-diverse people are experts of their own identity and should be involved in all aspects of research and clinical care; (3) research is needed to understand the disparities autistic transgender people face; (4) attempts to restrict autistic transgender people's access to gender care are unsupported by existing research; (5) adult gender care may benefit from incorporating universal design principles and neurodiversity-affirming strategies to reduce barriers to care and improve clinician-client communication in treatment delivery and the informed consent process; (6) cross-cultural and cross-societal research will improve best care practices in diverse contexts; (7) research and advocacy must be inclusive across ethnoracial identities, including in leadership and perspectives represented; and (8) a life span developmental framework is needed for adult research in this field.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.387
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations36
Published2023
Admission routes1
Has abstractyes

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