Bibliographic record
Abstract
Making smart savings choices is critical to ensuring Canadians have access to sufficient and secure post-retirement incomes. Except for the working poor, Canadians must save a very high fraction of pre-retirement earnings every year – either through employer plans or private saving – to provide for reasonably adequate and assured retirement incomes. We estimate that most Canadians, should they wish to retire at age 65 and replace 70 percent of their working incomes, will need to save from 10 to 21 percent of their pre-tax earnings every year, if they save for 35 years. Although private retirement savings allow choice about retirement age and income, Income Tax Act limits on tax-recognized savings would prevent many earners from accumulating sufficient RRSP savings over 33 years (by age 63) to securely replace 70 percent or more of their working incomes. The authors are grateful to the members of the Pension Series Advisory Group of the C.D. Howe Institute for their thoughtful comments and suggestions on this paper; and in particular to James Pierlot and Faisal Siddiqi at Towers Watson for providing us with annuity factors. As Canada’s babyboom generation approaches retirement age, public concern about the adequacy of
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.453 | 0.223 |
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".