Characteristics of Two-Year College Students on the Autism Spectrum and Their Support Services Experiences
Bibliographic record
Abstract
Approximately 80% of college-going youth with autism in the US attend a 2-year college at some point. These community-based, universally accessible institutions offer both academic and vocational courses and have experience in teaching diverse learners. This study used nationally representative survey data from the National Longitudinal Transition Study-2 to describe the characteristics and services experiences of adults with autism who attended postsecondary education after high school, focusing on those who attended a 2-year college. Over 60% of those who attended 2-year colleges had little to no trouble conversing or performing functional skills like counting change during high school, and extracurricular participation was common (93.8%). Most 2-year college attenders (85.7%) were able to navigate to places outside the home versus 43.9% of those with no postsecondary education. Over half took vocational courses at 2-year colleges, while one-quarter pursued academic study. Less than half (48.6%) of those who disclosed their disability to the school reported receiving services, accommodations, or other help. Most (87.3%) felt they received enough help, but fewer (68.0%) felt the services they received were useful. Future research should delineate specific needs of students with autism in 2-year college settings and identify what supports are needed to improve persistence and completion rates.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".