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Record W2151848795 · doi:10.1353/dem.0.0024

Child poverty and changes in child poverty

2008· article· en· W2151848795 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDemography · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsUniversity of OttawaStatistics Canada
FundersUNICEF
KeywordsPovertyEarningsEconomicsChild povertyDemographic economicsLabour economicsCurrent Population SurveyDevelopment economicsPopulationEconomic growthDemography

Abstract

fetched live from OpenAlex

This article offers a cross-country overview of child poverty, changes in child poverty, and the impact of public policy in North America and Europe. Levels and changes in child poverty rates in 12 Organisation for Economic Co-operation and Development (OECD) countries during the 1990s are documented using data from the Luxembourg Income Study project, and a decomposition analysis is used to uncover the relative role of demographic factors, labor markets, and income transfers from the state in determining the magnitude and direction of the changes. Child poverty rates fell noticeably in only three countries and rose in three others. In no country were demographic factors a force for higher child poverty rates, but these factors were also limited in their ability to cushion children from adverse shocks originating in the labor market or the government sector. Increases in the labor market engagement of mothers consistently lowered child poverty rates, while decreases in the employment rates and earnings of fathers were a force for higher rates. Finally, there is no single road to lower child poverty rates. Reforms to income transfers intended to increase labor supply may or may not end up lowering the child poverty rate.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.443
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.267
Teacher spread0.246 · 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