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Record W2967901995 · doi:10.3138/cpp.2019-003

Policy Options for Retargeting the Canada Child Benefit

2019· article· en· W2967901995 on OpenAlexaffvenueabout
Jonathan R. Kesselman

Bibliographic record

VenueCanadian Public Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAdditionalityIncentiveChild povertyPovertyDiscretionPublic economicsCashChild supportDistribution (mathematics)Poverty reductionTransfer (computing)BusinessCash transfersEconomicsPolitical scienceFinanceEconomic growthComputer scienceMicroeconomics

Abstract

fetched live from OpenAlex

The Canada Child Benefit (CCB) is the nation’s second largest cash transfer program, and it contributes significantly to reducing child poverty. The program could be further targeted to poverty reduction either through federal program changes or by giving each province the discretion to vary its parameters on a cost-neutral basis. This article describes the CCB, documents the eight provincial child benefit programs, and investigates various scenarios for federal reform of or provincial variation in the CCB. The article presents simulated impacts of the cost-neutral policy scenarios on distribution and incentives for various groups, with a special focus on sole-parent families, and it assesses major related policy considerations.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0040.001
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.016
GPT teacher head0.256
Teacher spread0.241 · 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 designTheoretical or conceptual
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

Citations12
Published2019
Admission routes3
Has abstractyes

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