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The impact of the Self‐Sufficiency Project on the employment behaviour of former welfare recipients

2010· article· en· W2143551151 on OpenAlexaffvenueabout
Jeffrey Zabel, Saul Schwartz, Stephen G. Donald

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsEarningsSubsidyRandom assignmentWelfareSelf-employmentEconomicsRandomized experimentLabour economicsDemographic economicsPercentage pointOrder (exchange)EntrepreneurshipFinanceMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract The Self‐Sufficiency Project (SSP) was a Canadian randomized trial in which the program group had 12 months to find full‐time employment in order to qualify for a subsidy that roughly doubled their pre‐tax earnings for the next three years. We find evidence of significant impacts of SSP on non‐employment and employment durations. For the treated group, simulation results show an impact on the employment rate at 52 months after random assignment in the range of 7 to 11 percentage points; this is approximately a 25% increase in the employment rate compared with having no treatment in place.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.081
GPT teacher head0.237
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2010
Admission routes3
Has abstractyes

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