The Development and Evaluation of a Cross-Context Employment Program for Autistic Adolescents
Bibliographic record
Abstract
Vocational programs typically focus on building the skills of autistic youth. However, there is growing recognition that the supportive environment (or ecosystem) around an individual plays an important role in finding and maintaining work. Programs at the ecosystem-level can be established by coordinating support before high school ends. Cocreation of a vocational program by support providers can facilitate an integrated effort to prepare autistic youth for employment. In this study, we describe and evaluate the Job-Train Program (JTP), a vocational program for autistic high school students codesigned with educators and a community-based social services agency. A school board, community-based social services agency, and academics partnered to cocreate JTP. JTP combined skill teaching and paid supported employment on a university campus. This pilot study evaluated JTP using qualitative and quantitative data. Twelve autistic youth were recruited, aged 15–18 years (10 males, 2 females) with an average intelligence quotient of 101.9 (standard deviation = 14.4), from the Wechsler Abbreviated Scale of Intelligence-2. Youth and parents completed self-report measures (pre–post), including the primary outcome, Canadian Occupational Performance Measure (COPM). Post-JTP, interviews, focus groups, and surveys collected additional information from youth ( n = 11), parents ( n = 10), job coaches ( n = 5), and employers ( n = 8). Youth COPM scores indicated significant improvements in self-perceived ratings of skill performance ( z = −2.5, p = 0.01) and satisfaction ( z = −2.6, p = 0.01). Qualitative data corroborated COPM results noting youth skill improvements in self-esteem, independence, communication, and understanding work. Findings demonstrated a promising vocational training model for autistic high school students informing the development of integrated service pathways to support preparation for employment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".