Canadian Mapping of Autism Specific Supports for Postsecondary Students
Bibliographic record
Abstract
Background Many autistic students have a variety of strengths and the desire to succeed in postsecondary education. Nonetheless, most autistic students report not receiving adequate support in postsecondary education to ensure their success. Students also report difficulty in navigating complex institutional systems. We conducted an environmental scan of autism-specific supports (e.g., website information, transition programs, peer mentoring) available to autistic students within Canada’s publicly-funded postsecondary institutions. We also examined distribution of autism-specific supports across institutional type (i.e., university, junior college, technical/vocational) and geographic region. Method A Boolean search strategy was used to collect data from institutional websites. Results Of the 258 publicly-funded postsecondary institutions in Canada, only 15 institutions (6%) had at least one support. Of the 15 institutions identified, the most common autism-specific support included information on the institution’s website (67%), followed by transition to university support (47%), social group(s) (33%), peer mentoring (27%), specialist tutoring and support with daily living (20%), transition to employment support (13%), and student-led societies and autistic student advocate (7%). In general, universities and institutions in Central Canada (i.e., Ontario) had a disproportionate number of provisions. Conclusions There are promising advances with respect to autism-specific supports in postsecondary institutions across Canada. We recommend further research to better understand how students access these supports and more comprehensive evaluations of such supports, specifically informed by collaborations with autistic students.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.015 | 0.022 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".