Public Policy and the Economic Wellbeing of Elderly Immigrants
Bibliographic record
Abstract
In this paper we document the economic outcomes of elderly immigrants to Canada. Our objective is to describe the extent to which elderly immigrants may have low income (are “in poverty†) and their interactions with the Canadian income transfer system. The study has two main parts. First, using a combination of administrative and survey data, we describe the age dimensions of immigration to Canada since 1980, and the evolution of policies directed towards older immigrants (i.e., immigration selection, and eligibility for age-related social security programs). Second, using the SCF and SLID surveys spanning 1981 through 2006, we document the composition and levels of income for immigrants to Canada. We estimate the degree to which older immigrants support themselves, either through working, or living with relatives, as well as the degree that they rely on various income transfer programs, especially OAS, GIS, and Social Assistance (SA). We also summarize their overall living standards, and the extent to which they live in poverty (have “low incomes.†) Throughout the paper, we also explore the family dimensions to the outcomes of older immigrants: distinguishing between individual and family sources of income, as well as outlining differences in the living arrangements (family structure) of older immigrants, and the implications for measures of their well-being
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".