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Record W2699937900 · doi:10.1111/jomf.12421

Comparing Child Poverty Risk by Family Structure During the 2008 Recession

2017· article· en· W2699937900 on OpenAlexaffabout
David W. Rothwell, Annie McEwen

Bibliographic record

VenueJournal of Marriage and the Family · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsRecessionPovertyDemographic economicsWelfareChild povertyEconomicsGreat recessionDevelopment economicsEconomic growthLabour economics

Abstract

fetched live from OpenAlex

Children in nonmarried families are at greater risk for poverty and especially so during a time of macroeconomic recession. Using carefully harmonized data, the authors analyze child poverty among nonmarried families before and during the 2008 recession in five liberal welfare states: Australia, Canada, Ireland, the United Kingdom, and the United States. Although having similar demographic compositions, the authors document wide cross‐national variation in poverty risk based on marital status and gender of the household head. Through the recession, child poverty in Canada and the United Kingdom declined while it increased in Australia and Ireland and was largely unchanged in the United States. Decomposing changes within countries over time, family benefits in the form of income transfers play a major role in reducing poverty for nonmarried families. In all countries, children in cohabitating families were less protected from market instability.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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