For Whom the Retirement Bell Tolls: Accounting for Changes in the Expected Age of Retirement and the Incidence of Mandatory Retirement in Canada
Bibliographic record
Abstract
Data from the 2002 and 1994 General Social Survey are used to analyze the determinants of retiring due to mandatory retirement and the expected age of retirement in Canada. Changes between 1994 and 2002 are decomposed into two components, one attributable to shifts in the composition of respondents and the other to changes in the preferences and/or constraints of respondents. Changing preferences and constraints play a very important role for both outcomes. Specifically, we first indentify a 1.3 percentage point drop in the probability of retiring due to mandatory retirement between 1994 and 2002, with that drop due entirely to preference or constraint changes. These changes offset changes in the composition of the workforce, which were working to increase the probability of retiring due to mandatory retirement. Second, we find an increase of 3.7 years in the expected age of retirement between 1994 and 2002, with that increase being almost exclusively attributable to preference/constraint shifts. The implications of these findings for employers, employees, and policy-makers are discussed.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".