Bibliographic record
Abstract
Countries around the world are considering an increase to retirement ages in response to fiscal and demographic pressure on social security systems. However, concern may arise about the impact of such reforms on those who retire before the age of full social security entitlement. This paper addresses the question of how those stopping work before the age of benefit entitlement source their incomes and the extent to which they are able to avoid economic hardship. To do so, I study panels of Canadian men between 1993 and 2008 drawn from the Survey of Labour and Income Dynamics. The data allow a very detailed composition of income by source using a highquality income survey with annual information. These data are employed to make a novel calculation—determining the contribution of various supplemental income sources to lifting those not working at older ages out of a position of hardship. I find that demographic, health, and job characteristics are not very predictive of early retirement, and that those who retire early before the age of public pension entitlement are a very diverse group. Over half of the early retiring men I study who initially seem to suffer hardship before benefit entitlement are lifted out of hardship when other resources are accounted for.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".