Not in My Schoolyard: Disability Discrimination in Educational Access
Bibliographic record
Abstract
Disabled people constitute the largest minority group in the United States, and disability discrimination is prohibited under federal law. Nevertheless, disability has received limited attention in the sociology of discrimination. We examine disability discrimination in an important gatekeeping interaction: access to public education. In an audit study of more than 20,000 public schools, we sent emails to principals from fictitious prospective parents asking for a school tour, varying the child’s disability status and gender and the parent’s race. Principals were significantly less likely to respond when the child had a disability, especially when the email came from a Black (rather than White) parent. A survey experiment with 578 principals revealed possible mechanisms. Principals viewed disabled students as more likely to impose a significant burden on schools, but disabled Black students faced an additional disadvantage due to stereotypes of their parents, who were perceived to be less valuable future members of the school community in terms of fundraising, volunteering, and other forms of engagement to support the school. Our results highlight that discrimination against people with disabilities begins long before the labor market and illuminate how the intersection between disability and race shapes inequalities in educational access.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".