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Record W3137995390 · doi:10.15273/jue.v11i1.10869

Activists in Red Capes: Women's Use of The Handmaid's Tale to Fight for Reproductive Justice

2021· article· en· W3137995390 on OpenAlexvenueno aff
Madeline Carrola

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsDystopiaGender studiesPoliticsScholarshipParallelsSymbol (formal)White (mutation)Economic JusticeSociologyPolitical scienceMedia studiesLaw

Abstract

fetched live from OpenAlex

This paper examines women’s use of the notable red and white handmaid costume from Margaret Atwood’s The Handmaid’s Tale at political demonstrations following the 2016 U.S. presidential election. Drawing on ten in-depth ethnographic interviews with women who participated in handmaid chapters, my study finds that interviewees began to wear the handmaid costume at political protests because they increasingly saw parallels between the United States and Gilead—the totalitarian society in Atwood’s novel—as a result of the 2016 election. Participants viewed the costume as a feminist symbol that enabled them to increase awareness about women’s issues, particularly related to reproductive justice. Additionally, interviewees saw the anonymity of the costume as a way to represent all women, especially those who were unable to participate in such protests. This study extends existing scholarship on social movements and women’s activism in the United States by exploring women’s reasons for involvement in this new form of protest and their use of dystopian popular culture as the basis of their performance activism.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.465
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.086
GPT teacher head0.298
Teacher spread0.213 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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