The Employment Quality of Persons with Disabilities: Findings from a National Survey
Bibliographic record
Abstract
PURPOSE: Labour market integration is a widely accepted strategy for promoting the social and economic inclusion of persons with disabilities. But what kinds of jobs do persons with disabilities obtain following their integration into the labour market? In this study, we use a novel survey of workers to describe and compare the employment quality of persons with and without disabilities in Canada. METHODS: We administered an online, cross-sectional survey to a heterogeneous sample of workers in Canada (n = 2,794). We collected data on sixteen different employment conditions (e.g., temporary contract, job security, flexible work schedule, job lock, skill match, training opportunities, and union membership). We used latent class cluster analysis to construct a novel typology of employment quality describing four distinct 'types' of employment: standard, portfolio, instrumental, and precarious. We examined associations between disability status, disability type, and employment quality. RESULTS: Persons with disabilities reported consistently lower employment quality than their counterparts without disabilities. Persons with disabilities were nearly twice as likely to report low-quality employment in the form of either instrumental (i.e., secure but trapped) or precarious (i.e., insecure and unrewarding) employment. This gap in employment quality was particularly pronounced for those who reported living with both a physical and mental/cognitive condition. CONCLUSION: There are widespread inequalities in the employment quality of persons with and without disabilities in Canada. Policies and programs aiming to improve the labour market situation of persons with disabilities should emphasize the importance of high-quality employment as a key facet of social and economic inclusion.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".