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Record W3121678854 · doi:10.3386/w23380

How do the U.S and Canadian Social Safety Nets Compare for Women and Children?

2017· report· en· W3121678854 on OpenAlexaboutno aff
Hilary Hoynes, Mark Stabile

Bibliographic record

VenueNational Bureau of Economic Research · 2017
Typereport
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPolitical science

Abstract

fetched live from OpenAlex

The past 25 years has seen substantial change in the social safety nets for families with children in the US and Canada. Both countries have moved away from cash welfare but the US has done so relying more exclusively on inwork benefits with work requirements. This paper examines this evolution across the two countries and examines the effects on employment and poverty. In particular, we focus on the two largest programs over this period: the U.S. EITC and the Canadian NCB/CCTB. In light of these policy changes, we examine trends in employment and poverty of the most affected families --single mothers with less than a college degree --across the two countries. We find that employment improved substantially in both countries, absolutely and relative to a control group of single women without children. The cross-country differences in relative trends are mainly explained by differences in the labor market conditions. Poverty rates for single mothers also declined in both countries with more of the decline coming through market income in the U.S. and benefit income in Canada.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.234
GPT teacher head0.473
Teacher spread0.239 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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