Evaluation of employment-support services for adults with autism spectrum disorder
Bibliographic record
Abstract
The employment rate among persons with autism spectrum disorder has been noted as unacceptably low. Employment-support services are increasingly linked to the potential for favorable job outcomes, yet little is known about employment-support practices and the outcome of these interventions. This mixed-methods study examined employment-support resources for persons with autism spectrum disorder. An online survey was completed by 137 senior clinicians or administrators in employment-support programs in Canada. Additionally, 122 follow-up interviews were conducted with individuals with autism spectrum disorder (n = 71) and their parents/caregivers (n = 51). Findings indicate that the quality and beneficial impact of employment-support services for adults with autism spectrum disorder may be more favorably perceived by employment-support personnel than by individuals with autism spectrum disorder and their families. Furthermore, employment-support personnel were more disparaging about autism spectrum disorder vocational support capacity within their community, compared to their own programs. Individuals with autism spectrum disorder and their families seek services that support both accessing and retaining employment. Capacity-building in employment support for youth and adults with autism spectrum disorder is recommended, based on a reported insufficiency of, and a lack of evidence guiding, existing services. Program recommendations and an emerging model for integrated vocational support in autism spectrum disorder are offered.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".