Holes in the Social Safety Net: Poverty, Inequality and Social Assistance in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it