The prevalence and composition of asset poverty in Canada: 1999, 2005, and 2012
Bibliographic record
Abstract
A household is considered asset poor if its assets (financial assets or net worth, taken separately) are insufficient to maintain well‐being at a low‐income threshold for 3 months. We provide the first national‐level estimates of asset poverty for Canada, using the 1999, 2005, and 2012 cycles of the Survey of Financial Security, and juxtapose these estimates with income poverty. The analysis provides new insight into economic insecurity by showing that asset poverty rates are consistently two to three times higher than income poverty rates. In addition to the prevalence of asset poverty across socio‐demographic groups, we analyzed how the composition of the poor change over time. Age and geography shape the risk for asset poverty in distinct ways. We found that while education appears to play a comparable role in shaping both income poverty and asset poverty, immigration places Canadians at a relatively higher risk of income poverty but not asset poverty. Key Practitioner Message: • Practitioners ought to consider assets as well as income in assessing economic vulnerability; • Asset poverty levels are 2–3 times higher than income poverty levels; • Certain groups (e.g., immigrants) may be income poor but maintain sufficient assets.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".