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Record W4390979383 · doi:10.1177/00207152231222919

Multidimensional domestic gender inequality and the global diffusion of women’s ministries, 1975–2015

2024· article· en· W4390979383 on OpenAlexvenueno aff
Juan J. Fernández, Sílvia Claveria, Margarita Torre

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
FundersAgencia Estatal de Investigación
KeywordsFeminization (sociology)PoliticsArgument (complex analysis)InequalityOpportunity structuresElitePolitical scienceDemographic economicsSociologyEconomicsGender studies

Abstract

fetched live from OpenAlex

Since the 1970s, many countries have passed policy and institutional reforms to promote gender equality and the wellbeing of women. The global diffusion of gender and women’s ministries constitutes a manifestation of this process. However, our understanding of the diffusion of this organizational form is very limited. To fill this gap, we examine the adoption of cabinet-level, women’s ministries worldwide, between 1975 and 2015. Our argument builds on the fact that, within a given country, gender (in)equality is heterogeneous across the economic, political and social domains, and that shifts in women’s descriptive political representation and feminization of the labor force hasten the adoption of these ministries. As women expand their formal political power, they are better able to foster the perception of a linked fate and promote the creation of women’s machineries. Moreover, rapid feminization of the labor force increases the opportunity costs of all forms of gender discrimination and improves women’s collective socio-political economic resources to act against all forms of discrimination. Commensurate with our argument, penalized maximum likelihood fixed-effects (PML-FE) models indicate that countries which observe faster increases in women’s presence in the political elite and feminization of the labor force are more likely to adopt a women’s ministry.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.076
GPT teacher head0.441
Teacher spread0.365 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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