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Record W4221128792 · doi:10.1159/000524015

Measuring Autistic Writing Skills: Combining Perspectives from Neurodiversity Advocates, Autism Researchers, and Writing Theories

2022· article· en· W4221128792 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.

Bibliographic record

VenueHuman Development · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutismPsychologySociocultural evolutionDevelopmental psychologyCognitionCognitive scienceCognitive psychologySociologyNeuroscience

Abstract

fetched live from OpenAlex

Autism and writing are commonly discussed independently as complex, multifaceted entities. However, studies examining their intersections are limited and often oversimplify the nuances innate to both topics. This paper focuses on the complexities involved in studying autistic individuals’ foundational writing skills (i.e., transcription and text generation skills) by drawing on theories of writing and autism grounded in perspectives from the neurodiversity movement. We frame our discussion around the complex sociocultural and cognitive factors important to writing by drawing on the Writer(s)-within-Community model. Our discussion highlights findings and trends among observational and intervention research studies as well as offers suggestions for future research guided by the ongoing reconceptualization and understanding of autistic development. In doing so, we argue that future research should look beyond written products as the only measure of writing development and beyond a diagnosis of autism as the indicator of atypical written language development.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.084
GPT teacher head0.328
Teacher spread0.244 · 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