An Interpretative Phenomenological Analysis Exploring the Lived Experiences of Autistic Undergraduate Psychology Students Engaging and Integrating within UCalgary
Bibliographic record
Abstract
Research studying autism has often had a negative, deficit-based outlook on the diagnosis. Additionally, many studies highlight barriers or challenges encountered by the autistic population (McLeod et al., 2021; Shembri-Mutch et al., 2024). Another factor leading to knowledge-gaps in the vast collection of autism research is a disproportionate lack of autistic representation throughout all stages of the research process (Leadbitter et al., 2021). Currently, there is a gap in accessible post-secondary educational research regarding how neurodiverse individuals experience and engage with university life and integrate within the larger campus community. Neurodiversity (or neurodivergence) is a term that describes a range of neurodevelopmental disorders, including autism, and is an understanding that brain differences among people are a natural and valuable part of human diversity (Public Health Agency of Canada, 2024).
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".