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Record W4281626084 · doi:10.1080/14680777.2022.2080751

“Eight Tory leadership candidates declare themselves feminists”: feminism and political campaigns

2022· article· en· W4281626084 on OpenAlexafffundabout
Diretnan Dikwal‐Bot, Kaitlynn Mendes

Bibliographic record

VenueFeminist Media Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFeminismMainstreamGender studiesSociologyPoliticsRhetoricPolitical scienceEmancipationHegemonyContext (archaeology)Media studiesLaw

Abstract

fetched live from OpenAlex

This study examines the co-optation of feminism by politicians. Adopting a case study approach, we explore three contemporary leaders who declared themselves feminists during political campaigns: Canadian Prime Minister Justin Trudeau, Mayor of London Sadiq Khan, and British Prime Minister Boris Johnson. We analyse how these politicians communicated a feminist identity during and after electoral campaigns. Drawing from a thematic analysis of 503 international mainstream news articles, Instagram feeds, and selected Tweets we demonstrate how all three politicians reduce “feminism” to a neoliberal political theory that is neither radical nor revolutionary, but primarily focused on redistributive inequalities and ideals of getting women at the table. In this regard, we argue that the ambition to address “gender pay gaps” or achieve “gender-balanced cabinets” is inadequate in the project of gender emancipation. Using the concept of co-optation, we contribute to a critical interrogation of feminism in the mainstream media by providing insight into how self-identified male politicians engage with neoliberal, popular, and mainstream feminist rhetoric and action which provides them with both cultural and political capital. This draws attention to the context of political practice, the factors that shape such politicians’ behaviour in relation to hegemonic, neoliberal feminism, as well as the consequences of their actions on attaining gender justice.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.142
GPT teacher head0.347
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 teacher head, not a consensus.

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

Citations3
Published2022
Admission routes3
Has abstractyes

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