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Record W3084300059 · doi:10.18309/anp.v51i2.1406

Autistic university students’ accounts of interactions with nonautistic and autistic individuals: a rhetorical genre studies perspective

2020· article· en· W3084300059 on OpenAlexaffabout
J. P. Ballantine, Natasha Artemeva

Bibliographic record

VenueRevista da Anpoll · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsPerspective (graphical)HumanitiesPsychologySociologyDevelopmental psychologyPhilosophyArtVisual arts

Abstract

fetched live from OpenAlex

Increasing numbers of autistic students are enrolling in universities worldwide. These students are taught by mostly nonautistic instructors who try to support them in their learning of academic literacies, without always fully understanding this emerging group of neurodiverse students. Most research on the development of academic literacies, including academic writing, to date has not explored the lived experience of being an autistic student at university. In this small-scale qualitative exploratory pilot study, we draw on Rhetorical Genre Studies (RGS) to probe into the accounts of 12 autistic students from two Canadian universities regarding their interactions with nonautistic and autistic individuals at university. By analyzing the data from the RGS perspective, we have been able to establish and unpack the rhetorical nature of such social interactions. Understanding the rhetorical nature of these interactions provides a first step towards developing effective supports for autistic students learning to speak and write academically in the predominantly nonautistic contexts of universities.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.065
GPT teacher head0.332
Teacher spread0.267 · 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 designQualitative
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

Citations4
Published2020
Admission routes2
Has abstractyes

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