Employers’ attitudes toward persons with disabilities in the workforce: Myths or realities? Focus on Autism and Other Developmental Disabilities
Bibliographic record
Abstract
A review of literature on employers ' attitudes toward workers with disabilities was completed. Factors that may affect employers ' attitudes toward persons with disabilities in the workforce are provided, as well as a description of the methodologies used in the investigations. Although several key themes emerge, decades of employer attitudinal research has generally produced inconsistent findings due to variations in research design. Major legislative and philosophical forces during the past 30 years have attempted to enhance the participation of working-age Americans with disabilities in the competitive labor market. The public policy initiatives related to employers and/or work disability began in 1970 with the passage of the Occupational Safety and Health Act (OSHA). OSHA was followed by the Rehabilitation Act of 1973, state workers ' compensation enactments of the 1980s and 1990s, the Americans with Disabilities Act (ADA) of 1990, the Workforce Investment Act (WIA) of 1998, and the Ticket to Work and Work Incentives Improvement Act (TWWIIA) of 1999 (Hunt, 1999). The forces that have both paralleled and provided the impetus for passage of much of the legislation include the following: 1. significant changes in thinking regarding the vocational rehabilitation and employment potential
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".