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Record W1568025745 · doi:10.1111/caje.12409

Child cash benefits and family expenditures: Evidence from the National Child Benefit

2019· article· en· W1568025745 on OpenAlexaffvenueabout
Lauren Jones, Kevin Milligan, Mark Stabile

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGenerosityExploitCashPublic economicsDemographic economicsIncome SupportEarned income tax creditEconomicsChild healthHousehold incomeLow incomeLabour economicsBusinessTax creditFinanceMedicinePolitical science

Abstract

fetched live from OpenAlex

Abstract Income may improve child outcomes through two mechanisms: as a direct input into health and education, or indirectly, by reducing household financial stress. We exploit policy‐induced changes in refundable tax benefit income in Canada to study these two potential mechanisms. Our findings suggest that additional income may improve outcomes through both mechanisms: some benefit income is spent on direct education inputs, while some is spent on everyday items likely to improve the general conditions children face. Additionally, some families reduce spending on risky behaviour items. Spending responses to benefit generosity appear to vary by income and by child age.

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)0.015
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 score0.080
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.097
GPT teacher head0.212
Teacher spread0.115 · 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

Citations77
Published2019
Admission routes3
Has abstractyes

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