A creative non-fiction account of autistic youth integrated physical education experiences
Bibliographic record
Abstract
In the United States (US), the drive to integrate, or mainstream, disabled students into the same educational settings as their non-disabled peers has resulted in disparate opportunities and experiences. With that, more autistic youth than ever before are expected to assimilate into systems that are often not considerate of their needs and capabilities. We use a creative non-fiction narrative, crafted from qualitative interview data generated with eight autistic youth from the US, to explore subjective feelings of inclusion in integrated physical education contexts. Through Caleb’s story, we explore the complexity of relationships and interactions between autistic youth and their peers and teachers in physical education, and how they may influence the ways and extent to which autistic youth experience feelings of belonging, value and acceptance in physical education spaces. We also consider the role of teacher expectations, curriculum decisions and pedagogical actions in shaping the PE experiences of autistic students. Points of interestThis research explores autistic youths’ perspectives about their experiences in integrated PE contexts in the US and the inclusiveness of those experiences.Findings are presented in a story about Caleb, which shows what challenges within integrated physical education classes may look like from the perspective of autistic youth.Some autistic youth may experience challenges with the hyper-competitive culture often present in integrated physical education classes. Physical educators, like Mr. Jones, can exacerbate these challenges in physical education, perhaps unintentionally, by fostering competitive and physically aggressive behaviors.Caleb’s story highlights often unnoticed repercussions of being dumped into an integrated context, which include the (lack of) meaning he finds in his engagement in activities and (lack of) sense of belonging, acceptance, and value he finds in his overall experiences.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".