An Econometric Analysis of the Impact of the Self-Sufficiency Project on the Employment Behaviour of Former Welfare Recipients
Bibliographic record
Abstract
The Self-Sufficiency Project (SSP) was a Canadian research and demonstration project that attempted to make work pay for long-term income assistance (IA) recipients by supplementing their earnings. The long-term goal of SSP was to get lone parents permanently off IA and into the paid labour force. The purpose of this study is to evaluate the impact of SSP on employment and non-employment durations and its overall effect on employment rates. We focus on generating estimates of the effect of the treatment on the treated (TOT) where the treated are those in the program group who qualified for the earnings supplement by finding a full-time job during the qualifying period (a group we call the take-up group). To obtain a consistent estimate of TOT we follow the work of Ham and LaLonde (1996) and Eberwein, Ham and Lalonde (1997) in estimating a joint model of non-employment and employment durations that controls for unobserved heterogeneity and non-random selection into work and into the take-up group. We find evidence of significant impacts of SSP on non-employment and employment durations. Simulation results show a TOT on the employment rate at 52 months after baseline of approximately 4 percentage points; a 10 percent increase compared to the control group. Further, this estimate of TOT using the results from our econometric model is 5 percentage points higher than the estimate from the raw data.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".