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Record W3136351527 · doi:10.3386/w28556

The Effects of Child Tax Benefits on Poverty and Labor Supply: Evidence from the Canada Child Benefit and Universal Child Care Benefit

2021· report· en· W3136351527 on OpenAlexafffundabout
Michael Baker, Derek Messacar, Mark Stabile

Bibliographic record

VenueNational Bureau of Economic Research · 2021
Typereport
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversity of TorontoStatistics CanadaMemorial University of Newfoundland
FundersCanadian Institutes of Health ResearchUniversity of TorontoSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsPovertyChild povertyEconomicsChild careLabour economicsPublic economicsDemographic economicsMedicineEconomic growthNursing

Abstract

fetched live from OpenAlex

We investigate whether child tax benefits reduce child poverty and labor force participation among single mothers within the context of the 2015 expansion of the Canadian Universal Child Care Benefit (UCCB) and the 2016 introduction of the Canada Child Benefit (CCB). We compare single mothers to single childless women as single mothers have historically had the highest poverty rates. Our analysis indicates that both reforms reduced child poverty, although the Canada Child Benefit had the greater effect. We find no evidence of a labor supply response to either of the program reforms on either the extensive or intensive margins.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.370
Teacher spread0.307 · 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 teacher head, 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

Citations24
Published2021
Admission routes3
Has abstractyes

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