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Record W2232212688 · doi:10.1093/sp/jxv035

The Fading Goal of Gender Equality: Three Policy Directions that Underpin the Resilience of Gendered Socio-economic Inequalities

2015· article· en· W2232212688 on OpenAlexaff
Jane Jenson

Bibliographic record

VenueSocial Politics International Studies in Gender State & Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSociologyInequalityGender studiesPoliticsCare workGender equalitySocial inequalityRhetorical questionPolitical scienceWork (physics)

Abstract

fetched live from OpenAlex

Despite rhetorical commitment to gender equality as a fundamental value at international, supranational and national level, we continue to see economic and social inequalities in long-familiar areas. This article explores public policy communities' contribution to this resilience of inequalities in income, work and care by focussing on three responses to socio-economic restructuring and new social risks: labour force activation; the social investment perspective; treating gender as one of multiple discriminations. The article stresses the importance of making an analytic distinction between a policy discourse that displays “gender awareness” and one that identifies gender equality as a policy goal. By making this analytic distinction it is possible to identify a major change that has occurred in the last two decades in the universe of political discourse. This is the displacement of the gender equality discourse, despite rising gender awareness. The discourse on equality in income, work and care has been down-played within the universe of political discourse as other diagnostics either write gender equality out, rename women as “mothers,” or fold gender inequalities into a discursive frame of multiple and intersecting inequalities.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.006
Scholarly communication0.0000.000
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 head0.292
GPT teacher head0.454
Teacher spread0.161 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations39
Published2015
Admission routes1
Has abstractyes

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