Bibliographic record
Abstract
The recent report of the Expert Panel on Older Workers provided an important focus on retirement income policy. We comment here on the Panel’s recommendations that aim to support continued work by the elderly. We find that the focus on removing barriers to continued work is well-motivated, practical, and sensible. Particular attention must be paid to the full actuarial cost of reforms, however. Overall, the recommendations provide a sterling benchmark for future efforts to reform Canada’s retirement income system. The Expert Panel on Older Workers has produced a wide-ranging and ambitious report that touches on a number of important issues for older workers. The underlying premises of the report are that changes in the economy present unique challenges for older workers and that, in the future, elderly Canadians may need to work longer to maintain current trajectories of economic growth and living standards. The panel urges us to focus on older workers as a long-term but critical challenge for public policy research and action.1 The work of the Panel provides an important focal point for retirement income policy in Canada. The aim of increasing flexibility for retirement choices is well-chosen. It is important,
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".