Negative Effects of the Canadian GIS Clawback and Possible Mitigating Alternatives
Bibliographic record
Abstract
Abstract In Canada there are three main sources of government-provided retirement income: the Canada/Quebec Pension Plans (C/QPP), which have benefits and contributions based on earnings up to the Yearly Maximum Pensionable Earnings; Old Age Security (OAS), which is a fixed amount for most but does include a “clawback” of benefits for high-income individuals; and the Guaranteed Income Supplement (GIS), which is designed to supplement those persons with extremely low income. The annual GIS benefit is reduced, or clawed back, by 50 cents for every dollar of annual income the person has in retirement, including C/QPP and income from Registered Retirement Savings Plans (RRSPs) and other savings. OAS benefits are not included in determining the GIS clawback. The result of this is that low-income individuals who attempt to enhance their retirement replacement ratio actually see a decrease in government-provided support the more they save for retirement. Savings in an RRSP can effectively be taxed at more than 100% through corresponding reductions in the GIS, social housing, home care, GAINS (Ontario’s Guaranteed Annual Income Supplement), and other benefits that are based on one’s personal retirement income. This paper explores alternatives to the 50% GIS clawback, including a basic GIS exemption, a GIS clawback rate lower than 50%, and a combination of the two. The goal is to improve the fairness of the GIS and reduce the disincentive to save for retirement, without increasing the overall cost of the program significantly.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".