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Record W3121832781

When Can Experimental Evidence Mislead? A Re-Assessment of Canada's Self Sufficiency Project

2016· preprint· en· W3121832781 on OpenAlexaboutno aff
Chris Riddell, W. Craig Riddell

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCounterfactual thinkingIncentiveWelfareWorkforceWork (physics)EconomicsPublic economicsImpact evaluationControl (management)Actuarial scienceMicroeconomicsPsychologySocial psychologyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

The Self-Sufficiency Project was a well-known welfare-to-work experiment that provided a generous but time-limited financial incentive to leave welfare and enter the workforce. Experimental evidence showed large short-term impacts but no lasting effects. We argue that these conclusions need to be re-assessed. Policy changes implemented during the SSP implied the behavior of the control group did not provide an appropriate counterfactual. We estimate the impacts the financial incentive would have had in a stable policy environment. This re-assessment leads to significant changes in the lessons previously reached. Our study demonstrates that experimental findings need to be interpreted with care.

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)0.495
metaresearch head score (Gemma)0.688
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score0.623

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4950.688
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.004
Science and technology studies0.0060.025
Scholarly communication0.0080.009
Open science0.0100.007
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.058
GPT teacher head0.376
Teacher spread0.319 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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