Policy Changes and the Labour Force Participation of Older Workers: Evidence from Six Countries
Bibliographic record
Abstract
In response to the anticipated pressures of population aging, national governments and supra-national bodies such as the Organisation for Economic Co-operation and Development (OECD) and the European Union (EU) have promoted policies to encourage the labour force participation of older workers. The recent elimination of mandatory retirement in Ontario is an example of such a policy, and others include changes to national pension systems and changes to disability and employment insurance programs, active labour-market policies, and the promotion of phased or gradual retirement. This paper reviews the different policy approaches taken in the six countries included in the Workforce Aging in the New Economy (WANE) project, placing Canadian policy approaches in relation to those taken in Australia, Germany, the Netherlands, the United Kingdom, and the United States. From the life course perspective, the policy approaches discussed here do not consider the heterogeneity of older workers' life courses or the related domains of health and family. As well, the changes made thus far do not appear likely to lead to increased labour force participation by older workers, and some may leave older workers at greater risk of low income and low-wage work.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 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".