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Record W4401567126 · doi:10.1080/00336297.2024.2386319

Valuable Diversity or Pathological Problem?: A Comparative Thematic Analysis of Self-Advocate and Adapted Physical Activity Teachings About Autism

2024· article· en· W4401567126 on OpenAlex
An Nguyen, Danielle Peers

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueQuest · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Alberta
FundersCanada Research Chairs
KeywordsAutismPsychologyNeurotypicalDiversity (politics)Emic and eticThematic analysisDevelopmental psychologySociologyQualitative researchAutism spectrum disorderSocial science

Abstract

fetched live from OpenAlex

This article offers a comparative thematic analysis of two datasets: the online writings of Autistic self-advocates on navigating neurotypical programs (emic dataset), and discussions on autism within the most widely circulated undergraduate Adapted Physical Activity (etic dataset). Our 3 themes describe some of the most significant ways that APA textbooks differed from the teachings of Autistic self-advocates: 1) Writing in Categorical Imperatives, 2) Problematizing and Pathologizing Autism and Autistic Characteristics, and 3) Promoting ABA and Autism Speaks. We end with a discussion of how these findings demonstrate a dissonance not only between APA and Autistic knowledges, but also between APA textbook approaches to Autism and APA’s stated core values, including dignity, choice, self-determination, and self-advocacy.

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 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 score0.673
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.087
GPT teacher head0.363
Teacher spread0.277 · 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