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Record W3196782326 · doi:10.1386/cc_00029_1

Fracking, fashion and the environmental activism of Vivienne Westwood

2021· article· en· W3196782326 on OpenAlexaff
Aidan Moir

Bibliographic record

VenueClothing Cultures · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArt, Politics, and Modernism
Canadian institutionsYork University
Fundersnot available
KeywordsEnvironmentalismPoliticsIconPolitical activismVariety (cybernetics)Political scienceMedia studiesLawSociology

Abstract

fetched live from OpenAlex

Vivienne Westwood frequently utilizes her iconic status to advocate for a variety of social, political and economic issues (). Since 2008, environmental politics, climate change and fracking policies have been the focus of her activism. Westwood regularly attends anti-fracking protests, such as in 2015, when she gained significant news attention for driving a tank across British Prime Minister David Cameron’s lawn. This article explores the possibilities of Westwood’s design activism within visual culture to communicate the grave environmental consequences of fracking and climate change. In addition to her political activities, Westwood has incorporated an environmental critique into her fashion collections, such as transforming her 2015 London Fashion Week performance into an anti-fracking protest. Westwood consequently draws upon her privileged status as a cultural icon to position her runway and subsequent media attention as a platform encouraging critical debate in regard to ethical fashion and environmental change.

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)0.002
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.009
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.020
GPT teacher head0.235
Teacher spread0.215 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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