Some Perspectives on Changing the Pension System
Bibliographic record
Abstract
This paper addresses the perceived difficulties in making changes to the retirement income system as a whole. We focus on public system reforms and observe some of the changes that have taken place in Canada and in a number of OECD (Organisation for Economic Co-operation and Development) countries. Reforming social institutions is never easy. We examine some of the preconceived notions or “myths” that create public resistance to reform. Further, the complexity of the retirement income system in Canada makes consensus difficult to achieve. Nonetheless, we argue that pension reforms can and should be made to ensure the delivery of promised benefits, and we demonstrate the efficacy of smaller-scale reforms.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.043 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".