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Record W4402557421 · doi:10.29173/spectrum284

Autistics, Myths, and Robots

2024· article· en· W4402557421 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSpectrum · 2024
Typearticle
Languageen
FieldPsychology
TopicSocial Robot Interaction and HRI
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMythologyRobotComputer scienceCommunicationArtificial intelligencePsychologyArtLiterature

Abstract

fetched live from OpenAlex

Abstract Despite growing awareness, misconceptions about autism (also known as autism spectrum disorder or ASD) persist within science, academia, and popular culture. These misconceptions perpetuate harmful stereotypes that contribute to the ongoing stigma, exclusion, and isolation experienced by autistic individuals. A significant barrier to overcoming these challenges is the underrepresentation of autistic voices across multiple fields and disciplines, making it difficult to effectively challenge and transform prevailing social norms and attitudes about disabilities and neurological differences. While efforts are being made by advocates to improve representation through community-based participatory research and coproduction models, the arts remain a particularly powerful yet underutilized tool for disrupting problematic discourse. Through creative expression, the arts offer a unique avenue to subvert reductionistic pathologies, dehumanizing language, and unfavorable depictions of autism that have been deeply engrained in both academic and cultural discourse. This poem critically engages with widespread stereotypes, using sarcasm and humor to reclaim and reshape existing depictions of autism. By doing so, it aims to empower fellow autistic individuals to challenge these narratives and express their own experiences through whatever creative mediums resonate with them, ultimately offering a more nuanced and representative understanding of autism in the process. Keywords: Arts, neurodiversity, critical autism studies, representation, stereotypes, subversion Author’s Note As an autistic scholar and artist, I rely on a combination of lived experience, community involvement, and research training within this creative piece. A significant source of inspiration comes from the 2SLGBTQIA+ community, particularly their powerful reclamation of terms like “queer” that were once used as weapons of marginalization and exclusion. By embracing and redefining these terms, this community has subverted their original pejorative meanings, transforming them into symbols of identity, pride, and resistance. This act of linguistic reclamation not only disrupts the power dynamics of hate and oppression but also fosters a sense of solidarity. In a similar vein, my work seeks to challenge and overturn the derogatory labels and misconceptions that have been imposed upon autistic individuals, using creative expression as a means to redefine our realities. Historically, academic and societal discourses have often dehumanized autistic people through harmful and reductive descriptions, perpetuating what I refer to in this piece as “myths” about autism. Through this work, I critically deconstruct these demeaning representations, employing a sardonic lens to counter these narratives and expose their absurdity. Incorporating examples from my experiences as an autism and neurodevelopmental researcher, I seek to highlight and dismantle these entrenched misconceptions, including deficit-based models, problematic pathologies, and stigmatizing descriptions of autistic individuals. As someone who experiences echolalia (i.e., the repetition of words, phrases, and sentences) and who frequently incorporates pop culture references when communicating with others, this piece also serves as a homage to the songs, films, and television shows that resonate with me and my special interests. To ensure clarity and accessibility for readers, I have included detailed endnotes that explain both the research references and the various pop culture elements, providing a comprehensive overview of the content and its meaning.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.020
GPT teacher head0.363
Teacher spread0.342 · 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