The Effect of Education on the Occupational Status of Deaf and Hard of Hearing 26-to-64-Year-Olds
Bibliographic record
Abstract
In the last quarter of the 20th century, federal legislation sought to eliminate disability-based discrimination by requiring reasonable accommodations in school and the workplace. One result of this legislation has been increased access to U.S. colleges and universities by deaf and hard of hearing persons. The present article reviews the literature on employment of persons who are deaf or hard of hearing and reports results of a recent analysis that used the 2010 American Community Survey (U.S. Census Bureau, 2010a). It was found that significant gains in college attendance and graduation occurred during the period, with individuals who attained a college degree realizing increased employment and earnings relative to individuals who had not graduated. It was also found that college graduation helps reduce the gap between the earnings of deaf persons with a college degree and those of comparably educated hearing persons.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".