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Record W4240696058 · doi:10.1080/14616740500284417

What are we mainstreaming when we mainstream gender?

2005· article· en· W4240696058 on OpenAlexaboutno aff
Joan Eveline, Carol Bacchi

Bibliographic record

VenueInternational Feminist Journal of Politics · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsGender mainstreamingMainstreamingMainstreamGender studiesArgument (complex analysis)SociologyOntologyGender equalityPolitical scienceEpistemologyLaw

Abstract

fetched live from OpenAlex

In the policies and practices of gender mainstreaming, gender itself is a contested concept. This article examines versions of gender mainstreaming in two countries, focusing on approaches we term the Canadian and Netherlands models. We show how different understandings of gender are attached to different reform approaches, and intimate how particular ways of conceptualising gender inhibit the efficacy of the mainstreaming strategy. In order to increase that effectiveness we suggest that gender mainstreaming models incorporate a view of gender as a verb rather than as a noun, so that the focus is on the processes of gendering rather than on the static category of ‘gender’. We make the argument that such a shift could: a) incorporate a feminist ontology of the body; b) align an understanding of gender as an unfinished process with the ways in which those who make and implement policy experience gender mainstreaming as always partial and incomplete.

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)0.022
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.057
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.066
Scholarly communication0.0240.025
Open science0.0020.007
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.064
GPT teacher head0.362
Teacher spread0.299 · 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 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

Citations118
Published2005
Admission routes1
Has abstractyes

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