The Limitations of Disability Antidiscrimination Legislation: Policymaking and the Economic Well‐being of People with Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although Congress passed the A mericans with D isabilities A ct ( ADA ) to address, in large part, the declining economic well‐being of people with disabilities—twenty years later—the trend has not reversed. To shed light on this puzzle, we use multilevel models to analyze Current Population Survey data from 1988 through 2012 matched with state‐level predictors. We take a more nuanced approach than previous research and consider institutional factors related to the creation, enforcement, and interpretation of legislation, as well as individual demographics and employment situations. Our results show continual gaps in employment and earnings by disability status connected to the enactment of state‐level antidiscrimination legislation, the number of ADA charges brought to the Equal Employment Opportunity Commission, and the results of ADA court settlements and decisions. Our findings suggest a complex relationship between legislative intent and policy outcomes, showcasing the multilayered institutional aspects behind the implementation of disability antidiscrimination legislation.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| 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 it