Autism Summer Employment Program: An Evaluation of a Community-Based Pilot Program
Bibliographic record
Abstract
Background: The Autism (formerly Asperger) Summer Employment Program (ASEP) was a community-based pilot program designed to provide summer vocational support to autistic university and college students. The ASEP was the initiative of community agencies interested in identifying service gaps for autistic adults during transition periods, such as entering the workforce following post-secondary education. The current study reports on a program evaluation of the ASEP developed by a community agency in Toronto in which two workforce specialists provided ongoing training and support for 17 autistic adults over a four-month summer period. Twelve participants obtained paid employment, three obtained volunteer positions, and two were unsuccessful in obtaining summer placements. Methods: Evaluation of the ASEP was based on responses to a questionnaire by participants and reports from employers. Participants completed questionnaires before and after the program, while employers completed questionnaires at the end of the program. Results: Self-rated autism symptom severity was high and correlated with some self-reported job-related knowledge and skills. Participants reported a significant increase in their job-related knowledge and skills from pre- to post-program. At the conclusion of the program, employers reviewed participant’s job as "good" on average. When asked if participants would be considered for future employment, most employers responded positively, while some had some concerns. Conclusion: Overall, the results suggest that with appropriate support, successful summer vocational experiences are accessible to autistic students. Clinical implications are discussed.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".