The Canadian Elder Standard – Pricing the Cost of Basic Needs for the Canadian Elderly
Bibliographic record
Abstract
We determined the after-tax income required to finance basic needs for Canadian elders living with different circumstances in terms of age, gender, city of residence, household size, homeowner or renter status, means of transportation, and health status. Using 2001 as our base year, we priced the typical expenses for food, shelter, medical, transportation, miscellaneous basic living items and home-based long-term care for elders living in five Canadian cities. This is the first Canadian study of basic living expenses tailored to elders instead of adults in general, prepared on an absolute rather than a relative basis. We also accounted for an individual's unique life circumstances and established the varying effect that they have on the cost of basic expenses, particularly for home care. We found that the maximum Guaranteed Income Supplement and Old Age Security benefit did not meet the cost of basic needs for an elder living in poor circumstances.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; 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".