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Record W4413096960 · doi:10.1093/sp/jxaf026

Care Policy Determinants and Effects: Convergences and Divergences Across the Americas

2025· article· en· W4413096960 on OpenAlexaff
Cynthia J. Cranford, Flavia Marco Navarro

Bibliographic record

VenueSocial Politics International Studies in Gender State & Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScholarshipSituatedCare workLatin AmericansPoliticsIntersectionalityPolitical scienceSociologyWork (physics)Economic growthGender studiesEconomics

Abstract

fetched live from OpenAlex

Abstract This special issue contributes to scholarship on gendered policies by engaging interdisciplinary conversations, intersectional analyses, and global approaches in four ways. First, we analyze care policy determinants alongside care policy outcomes through a feminist political economy framework. Second, we focus on less studied meso-level determinants of social policies: feminist framings and feminist networks that connect global, regional, national, and local levels. Third, we analyze the effects of multisectoral care policies, including childcare and care for aging and disabled people and ranging from institutional care to home-based domestic work. Fourth, we bring new insights from Latin America together with those of North America, and from researchers situated in universities, policy spaces, or both, using multiple methods to analyze convergences in global care policy determinants alongside divergent effects across and within countries.

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)0.009
metaresearch head score (Gemma)0.018
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0020.006
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.059
GPT teacher head0.469
Teacher spread0.410 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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