Autistic university students’ accounts of interactions with nonautistic and autistic individuals: a rhetorical genre studies perspective
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".