The value of employment support services for adults on the autism spectrum and/or with intellectual disabilities: Employee, employer, and job coach perspectives
Bibliographic record
Abstract
BACKGROUND: Employment rates among individuals on the autism spectrum or with intellectual disabilities (ID) remain extremely low. Although job coaching services have contributed to successful employment for these individuals, few studies have examined the importance of such support, and even fewer have explored which services are valued most by stakeholders. OBJECTIVE: We examined the importance of employment support services through employee, employer, and job coach perspectives, and employee and employer satisfaction of job coach support. METHODS: A multiple-case study was designed with a community organization providing employment support to individuals on the autism spectrum or with ID, and their employers. Nine employee-employer-job coach triads evaluated the importance of specific services and rated their satisfaction with the job coach support. RESULTS: Services were rated as important, however, some discrepancies were observed between the groups in their ratings of services (e.g., soliciting regular feedback about the employee’s performance). Satisfaction was high for employees and employers; both groups indicated that they would recommend these services. CONCLUSIONS: Job coach support was highly valued by all groups, underscoring the need for these services to be widely available, and suggesting that this support may serve as a critical factor in improving employment outcomes among this population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".