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Record W2179593737 · doi:10.1111/caje.12134

Did Canadian welfare reform work? The effects of new reform strategies on social assistance participation

2015· article· en· W2179593737 on OpenAlexvenueaboutno aff
Nathan Berg, Todd Gabel

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)SanctionsDemographicsWelfareEconomicsWelfare reformPoint (geometry)Social assistanceSocial WelfarePublic economicsDemographic economicsLabour economicsEconomic growthPolitical scienceMarket economyDemographySociology

Abstract

fetched live from OpenAlex

Abstract This paper measures the extent to which declines in social assistance (SA) participation were associated with novel and aggressive reforms referred to as new reform strategies: work requirements, diversion, earning exemptions and time limits. Controlling for province‐specific benefit levels, eligibility requirements, GDP growth, labour market conditions and demographics, SA participation rates were more than one percentage point lower (equivalent to a 13% decline) in provinces with new reforms. Work requirements with strong sanctions had the sharpest negative associations. New reform strategies explain at least 10% of observed declines in SA participation, twice that of benefit levels and eligibility requirements.

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)0.008
metaresearch head score (Gemma)0.021
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0050.003
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.131
GPT teacher head0.238
Teacher spread0.107 · 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

Citations16
Published2015
Admission routes2
Has abstractyes

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