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Record W1966159370 · doi:10.1111/1467-7660.00262

Democratization and State Feminism: Gender Politics in Africa and Latin America

2002· article· en· W1966159370 on OpenAlexaff
Philomina Okeke‐Ihejirika, Susan Franceschet

Bibliographic record

VenueDevelopment and Change · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsAcadia UniversityUniversity of Alberta
Fundersnot available
KeywordsDemocratizationFeminismPoliticsState (computer science)Gender studiesDemocracyContext (archaeology)Latin AmericansPolitical scienceSociologyIdeologyPolitical economyLaw

Abstract

fetched live from OpenAlex

This article addresses the link between state feminism and democratization in the global South. The authors use the contrasting cases of Chile and Nigeria to show some of the factors that encourage women to exploit the opportunities presented by transitions to democracy, and link the outcome of state feminism to the strategies and discourses available to women during democratization. Based on evidence from the cases analysed, the authors propose that the strategic options available to women are shaped by at least three factors: (1) the existence of a unified women’s movement capable of making political demands; (2) existing patterns of gender relations, which influence women’s access to arenas of political influence and power; and (3) the content of existing gender ideologies, and whether women can creatively deploy them to further their own interests. State feminism emerged in Chile out of the demands of a broad–based women’s movement in a context of democratic transition that provided feminists with access to political institutions. In Nigeria, attempts at creating state feminism have consistently failed due to a political transition from military to civilian rule that has not provided feminists with access to political arenas of influence, and the absence of a powerful women’s movement.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.015
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.001
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 head0.139
GPT teacher head0.294
Teacher spread0.155 · 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 designNot applicable
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

Citations54
Published2002
Admission routes1
Has abstractyes

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