What to do About Seniors' Benefits in Canada: the Case for letting Recipients Take Richer Payments Later
Bibliographic record
Abstract
Ottawa should move to reform seniors' benefits in the upcoming budget by letting recipients choose richer payments, later, from the Old Age Security and Guaranteed Income Supplement programs if they wish. In the report, the author says letting OAS and GIS recipients delay take-up and rewarding those who do could contain program costs over time in a way that is less stressful to recipients than raising the universal eligibility age, and less discouraging to work and saving than intensifying clawbacks. The report models the impact of such reform on payments to each age cohort after it reaches age 65. Because a new cohort turns 65 each year, and the cohorts are getting bigger, Robson calculates that the reform could help Ottawa's bottom line well into the future, alleviating the pressure of aging on government finances and Canada's economy.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".