Earnings of persons with disabilities: Who earns more (less) from entrepreneurial pursuit?
Bibliographic record
Abstract
Purpose Persons with disabilities (PWD) are among the largest and most diverse minority groups and among the most disadvantaged in terms of employment. Entrepreneurial pursuit is often advocated as a path toward employment, inclusion, and equality, yet few studies have investigated earning variation among PWD. Design/methodology/approach The authors draw on social cognitive career theory (SCCT), and the disability employment and entrepreneurship literature to develop hypotheses about who among PWD are likely to earn more (less) from entrepreneurial pursuits. The authors then conduct analyses on the nationally representative sample of the Canadian Survey on Disability (CSD) by including all PWD engaged in entrepreneurial pursuit, and matching each to an organizationally employed counterpart of the same gender and race and of similar age and disability severity ( n ≈ 810). Findings Entrepreneurial pursuit has a stronger negative association with the earnings of PWD who experience earlier disability onset ages, those who report more unmet accommodation needs, and those who are female. Originality/value First, this study applies SCCT to help bridge the literature on organizational employment barriers for PWD and entrepreneurs with disabilities. Second, we call into question the logic of neoliberalism about entrepreneurship by showing that barriers to organizational employment impact entrepreneurial pursuit decisions and thereby earnings. Third, we extend the understanding of entrepreneurial earnings among PWD by examining understudied disability attributes and demographic attributes. Lastly, this study is among the first to use a matched sample to empirically test the impact of entrepreneurial pursuit on the earnings of PWD.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".