Twenty-Five Years After the ADA: Situating Disability in America’s System of Stratification
Bibliographic record
Abstract
Americans with disabilities represent a significant proportion of the population. Despite their numbers and the economic hardships they face, disability is often excluded from general sociological studies of stratification and inequality. To address some of these omissions, this paper focuses on employment and earnings inequality by disability status in the United States since the enactment of the 1990 Americans with Disabilities Act (ADA), a policy that affects many Americans. After using Current Population Survey data from 1988-2014 to describe these continuing disparities, we review research that incorporates multiple theories to explain continuing gaps in employment and earnings by disability status. In addition to theories pointing to the so-called failures of the ADA, explanations also include general criticisms of the capitalist system and economic downturns, dependence on social welfare and disability benefits, the nature of work, and employer attitudes. We conclude with a call for additional research on disability and discrimination that helps to better situate disability within the American stratification system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".