Mandatory retirement legislation: a constraint on transitions to retirement?
Bibliographic record
Abstract
Issues associated with retirement in general, and phased transitions into retirement in particular, are taking on increased importance for a variety of reasons. Outlines those reasons, paying particular attention to the practice of mandatory retirement. Presents age dependency ratios for the OECD to highlight the importance of these issues in the context of an ageing and longer-lived workforce relative to a smaller working age population. Then discusses the prevalence of mandatory retirement in Canada and the USA, and presents empirical evidence from Canada on variables associated with retiring because of mandatory retirement. The Canadian case is of particular interest, because mandatory retirement in Canada has generally not been banned, which is in marked contrast with the situation in the USA, where it has been banned as constituting age discrimination. The public and legal debate over the issue of mandatory retirement has also been extensive in Canada, and this debate may provide information for other countries dealing with the issue. Ends with an assessment of the extent to which mandatory retirement exerts a constraining influence on transitions into retirement. The essential argument is that its constraining impact is not as simple as it may initially appear. To the extent that mandatory retirement is an intricate part of the compensation and human resource function of firms, banning it can have important implications for those functions and, in turn, for transitions into retirement. The complexities of these issues and dramatically increasing old-age dependency ratios will ensure that this is an area of growing importance for public policy and human resource management.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".