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Record W2972818415

Evaluation of the Impact of the Increase in EI Allowable Earnings Pilot Project on Working While on Claim and Job Search Behaviour in Canada

2011· preprint· en· W2972818415 on OpenAlexaboutno aff
Stéphanie Lluis, Brian P. McCall

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typepreprint
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsReceiptDuration (music)SubsidyWork (physics)Demographic economicsRobustness (evolution)Actuarial scienceBusinessEconomicsLabour economicsEngineeringAccounting
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the impact of the change in allowable earnings proposed in a pilot project (WWOC) of the Canadian Employment Insurance system implemented in December 2005 in some Canadian regions on working while on claim behaviour and on job search behaviour. The WWOC pilot is expected to increase the subsidy to low earnings/part-time work. Search theory would predict that, all else equal, individuals would increase their intensity of search for these types of jobs. We find evidence that the WWOC pilot substantially increased the incidence and duration of work while on claim receiving full benefits and reduced the incidence and duration of working while on claim receiving no benefits for both men and women. We also find differences in the impact of the WWOC pilot on the job search behaviour of men. These results suggest that the WWOC pilot significantly encouraged working while on claim in low-paying jobs allowing receipt of full benefits. The WWOC pilot significantly reduced the number of hours looking for a job and reduced the likelihood of looking for only a full-time job (relative to looking for only a part-time job or either). These results are robust to the various robustness check analyses performed.

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)0.005
metaresearch head score (Gemma)0.016
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 score0.043
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.197
GPT teacher head0.441
Teacher spread0.243 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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