Equal Education, Unequal Jobs: College and University Students with Disabilities
Bibliographic record
Abstract
Are students with a permanent disability more likely to drop out of post-secondary education than students without a permanent disability? Once they are out of postsecondary education, do their experiences in the labour market differ? Answers to these questions are necessary to evaluate current policies and to develop new policies. This paper addresses these two questions using a unique data set that combines administrative records from the Canada Student Loans Program with survey responses. Our measure of permanent disability is an objective one that requires a physician’s diagnosis. The survey data supply information on the students’ education and labour market status. Simple descriptive statistics suggest that, compared to students without a permanent disability, students with a permanent disability are equally likely to drop out of postsecondary education, but less likely to be in the labour force and more likely to be unemployed. We use propensity score matching to address potential selection into the group of students who documented their disability. The results using propensity score matching are consistent with the descriptive statistics. Our story is one of an underpublicized success—the rising number of students with disabilities in postsecondary institutions and their equal likelihood of graduation—and a persistent problem—the continued disadvantage that people with disabilities, even those with the same educational attainment as people without disabilities, face in the labour market.
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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".