Health and Disability as Determinants for Involuntary Retirement of People with Disabilities
Bibliographic record
Abstract
The association of health and disability factors on the perception of involuntary retirement in Canada was investigated with a multivariate logistic regression analysis of the 2006 Participation and Activity Limitation Survey data. The study investigated the role that choice or control plays in the decision to retire. Study participants were adults, with disabilities, aged 45 to 74 and who retired during the period 2001-2006. The analysis revealed that health at the time of retirement was not significantly associated with the perception of involuntary retirement, whereas disability characteristics were strongly associated with the type of retirement when health and other characteristics were controlled. Further, persons with disabilities who had to permanently retire because of their condition were eight times more likely to retire involuntarily than those whose conditions did not force involuntary retirement, suggesting the importance that control over the retirement decision has on the perception of involuntary retirement.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".