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Feminist Whiteness

2020· book-chapter· en· W4250252177 on OpenAlexaboutno aff
Éléonore Lépinard

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsGender studiesSalience (neuroscience)SociologyFeminist philosophyIgnorancePoliticsWhite (mutation)Race (biology)Identity (music)AestheticsPolitical sciencePsychologyArtLaw

Abstract

fetched live from OpenAlex

Abstract This chapter focuses on feminist whiteness, a concept it introduces and defines as the product of a process of political subjectivation as a white feminist. The concept captures the various repertoires that white feminists elaborate to talk about—or rather actively ignore—race relations of power and their own privileged positions in this racial order. The chapter traces how white feminists are constituted as political subjects through their relationship to nonwhite feminists, and to those whom they perceive and label as “bad” feminist subjects. It shows that debates on Islamic veiling have operated a shift in feminist whiteness, from feminist whiteness as ignorance to feminist whiteness as an active participation in national identity and femonationalist discourses. It also shows that feminist whiteness is multiple and varies across contexts. In France and Quebec, white feminists use different repertoires to address race issues. Some work around or evade race, while others recognize its political salience. These different forms of feminist whiteness are articulated with specific moral dispositions and emotions.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0340.004

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 head0.032
GPT teacher head0.237
Teacher spread0.205 · 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
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooks→Same topicMigration, Refugees, and Integration→French-language works237,207→