Untapped potential: Perspectives on the employment of people with intellectual disability
Bibliographic record
Abstract
OBJECTIVE: While individuals with intellectual disabilities can make valuable contributions in community workplaces, they typically experience low rates of paid employment. The goal of this article is to explore the reasons for the limited involvement of this population in competitive employment, provide a rationale for including individuals with intellectual disabilities as employees, and propose policy, structural and attitudinal changes that would be necessary to include them more meaningfully in the workforce. METHODS: The authors conducted a review of the literature relevant to the key theoretical concepts of disability, employment, organizational management and inclusion. RESULTS: The analysis reveals a number of theoretical, philosophical, legal and business arguments for and against the inclusion of workers with intellectual disabilities as employees, and suggests system level changes needed to mitigate challenges to recruiting, hiring and retaining these workers. CONCLUSIONS: Changes to the employment situation for workers with intellectual disabilities will require major shifts in government policy, workplace practices and vocational preparation of youth with intellectual disabilities. Continued research is necessary to identify best practices.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".