Autism has been constructed as a White male category. Currently, the prevalence ratio is 4 males to every 1 female diagnosed with autism. Historically, research studies supported these gender diagnostic gaps by claiming a genetic or hormonal causation. However, more recent research suggests that the gap in diagnosis is the cause of diagnostic bias, and instead, autism looks very different in women and girls compared to boys. Because autism is assumed to be a male category, autism intervention supports in schools do not reflect the needs of autistic girls.
Missing from autism research are the narratives, perspectives, and expertise of autistic people and their care networks. The majority of autism research today comes from the psychological and epidemiology fields and examines causation and the biological factors of autism. Autism is constructed as a problem to be “solved” and the autistic person as someone to be “cured.” The majority of autism research is about autistic people rather than with autistic people. This research is framed by an intersectional Disability Studies (DS) theoretical stance that forefronts the experiences of disabled people and understands disability to be an essential aspect of a person’s identity, rather than a problem to be solved. Working narratively through multimodal data collection, this study privileges the sense making of three autistic women and honors their forms of expression and communication. The study also includes the perspectives of the participants’ mothers as essential aspects of their care networks. Through their stories, the expertise of autistic women is honored as essential to all conversations regarding schooling interventions for autistic youth. By exclusively focusing on women, I challenge the myth of autism as a male category and challenge a positivist autism research approach that ignores gender altogether.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-ym4m-rm59 |
| Date | January 2021 |
| Creators | Leeper, Rae |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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