How Do Older Laid-Off Workers Get By: Reemployment, Early Retirement, or Social Insurance Benefits?
Bibliographic record
Abstract
We investigate the post-layoff configuration of income sources and pathways of prime-age and older laid-off workers exhibiting a high degree of prior attachment. Using a unique Canadian administrative database that links the event of the involuntary layoff with detailed data on income receipt, we track all of their sources of income over an interval spanning five years after layoff. We conduct a multivariate statistical analysis of the incidence of relying on income from several alternative sources, specifically early retirement (both public and private), reemployment, self-employment, or reliance on social insurance benefits (other than pensions). The two most common states for laid-off workers who have not yet reached normal retirement age are early retirement and continued labour market activity. Our findings indicate that the older workers are at the point of layoff, the greater the likelihood is that they will rely on pension income as their primary income source. This incidence of reliance on pension income also increases with the number of years elapsed since the point of layoff.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".