Pension Coverage and Earnings Replacement Rates Among Canadian Couples
Bibliographic record
Abstract
Using data from the Longitudinal Administrative Database (LAD), this paper compares the earnings replacement rates achieved in retirement by a sample of married and common-law couples in which the husband was aged 55 to 57 in 1991. Emphasis is placed on the outcomes experienced by couples in which one spouse or both spouses had registered pension plan (RPP) coverage and by couples without RPP coverage. The earnings replacement rates achieved by couples without RPP coverage are more widely dispersed than those of couples with RPP coverage. When compared at the mid-points of the pre-retirement earnings distributions, the median earnings replacement rates of couples without RPP coverage are about three to six percentage points lower than those of couples with RPP coverage. In contrast, the average earnings replacement rates of couples without RPP coverage are generally six to twelve percentage points higher than those of couples with RPP coverage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".