Holes in the Social Safety Net: Poverty, Inequality and Social Assistance in Canada
Bibliographic record
Abstract
This report looks at Canada’s social safety net before the onset of the crisis caused by COVID-19 and collapsing oil prices. It sets the stage by reviewing trends in poverty and inequality between 1976 and 2018. The report examines the federal government’s Poverty Reduction Strategy and its success in reducing poverty for children and seniors. Working-age adults without children have experienced the smallest relative decrease in poverty and currently have the highest poverty rates among any age group. The report analyzes general eligibility criteria and work and training requirements for social assistance, and the adequacy of welfare. National trends show that welfare dependency has fallen significantly between 1998 and 2018. Other significant trends show an increase in the percentage of social assistance recipients reporting a disability, a growing proportion of single adults on welfare and a decrease in the number of families with children receiving social assistance. To reduce poverty and improve welfare adequacy, this report recommends increasing social assistance benefits, raising the minimum wage, improving earning supplements for low-wage workers and extending in-kind benefits to all low-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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".