Bibliographic record
Abstract
amount of attention focused on the economic conditions of Canada’s seniors (those aged 65 and over). In the past, many seniors had to work their whole life, and retirement was virtually unheard of. Those who were unable to save any money or to work because of illness and who had no family or friends to rely on spent their remaining years in poverty. Economic conditions for today’s seniors are very dif-ferent. Since the early 1980s, incomes have risen faster for those 65 and over than for those under 65 (Lindsay and Almey 1999). In fact, between 1981 and 1997, income rose about 18 % for seniors while declining for those aged 15 to 64. Nevertheless, seniors still have lower average incomes—not surprising given that most are no longer in the labour force and have no employ-ment income. However, the financial well-being of seniors is not determined by income alone; wealth also plays a part. While non-seniors are trying to build up their stock of wealth (buying homes, building up RRSPs or other investments), many seniors have already accumulated substantial wealth to draw on in times of need. This subject is certain to remain under close scrutiny as the proportion of seniors increases. Policy and program development centering on this group will no doubt figure prominently in forthcoming years, so it will be crucial to have a complete financial picture that high-lights their needs. Using the 1999 Survey of Financial Security (SFS) (see Data source and definitions), this article examines sources of income and wealth among Canada’s seniors. It also looks at their debts and preparedness for unexpected expenses. Additionally, two groups of seniors that potentially face financial insecurity are examined: unat-tached women and those whose expenses exceed their income.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.057 | 0.010 |
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".