Who was affected by new welfare reform strategies? Microdata estimates from Canada
Bibliographic record
Abstract
A heterogeneous mix of aggressive welfare reforms took effect in different provinces and years starting in the 1990s. Welfare participation rates subsequently declined. Previous investigations of these declines focused on cuts in benefits and stricter eligibility requirements. This article focuses instead on work requirements, diversion, earning exemptions and time limits – referred to jointly as new welfare reform strategies – while controlling for benefit levels, eligibility requirements, province-specific labour market conditions and GDP growth, as well as individual-level socio-economic information. Province-year-specific variation in new reform strategies produce estimates implying that their presence is associated with a large decline in welfare participation of 1.3 percentage points (14% relative to the unconditional mean participation rate of 9.2%). Our coding scheme generates new measures of policy variation that distinguish reductions in benefit levels and tighter eligibility restrictions from new welfare reform strategies, helping identify how different subpopulations responded to different kinds of welfare reforms. Estimates from 46 subpopulations demonstrate that immigrants, native Canadians, single parents and disabled people were substantially more likely to be affected by aggressive new attempts to limit welfare participation than other Canadians receiving social assistance.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".