Workplace Accommodations and the Labour Force Status of Persons with Disabilities
Bibliographic record
Abstract
Abstract Purpose The aim of the study is to examine the role of unmet needs for workplace accommodations (WPA) in the labour force status of persons with disabilities (PWD) aged 25–64 years. Methods The study used data from the 2017 Canadian Survey on Disability and multinomial logistic regressions to estimate the predicted probabilities of employment, unemployment, detachment from the labour force, and retirement. Product terms were used to examine if the association between unmet needs for WPA and these employment outcomes depended on severity of disability and age group. Results The findings show that the probability of employment was far lower for PWD with unmet needs for WPA than it was for their counterparts without unmet needs, after controlling for disability-related and sociodemographic characteristics. While having more severe disabilities associated with a lower employment rate, this occurred entirely in the context of unmet needs for WPA, as there was no difference between persons with milder and more severe disabilities without unmet needs. Unmet needs for WPA had age-specific consequences and were associated with a higher probability of unemployment and detachment from the labour force among PWDs aged 25–34 years and a higher probability of retirement among PWD aged 55–64 years. Conclusion Unmet needs for WPA are a barrier to the employment chances of many PWD and eliminating these needs could increase their inclusion in the labour force.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".