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Record W2333337729 · doi:10.1386/csfb.2.1-2.139_1

Ethical fashion and the exploitation of nonhuman animals

2011· article· en· W2333337729 on OpenAlexaff
John Sorenson

Bibliographic record

VenueCritical Studies in Fashion and Beauty · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsBrock University
Fundersnot available
KeywordsCrueltyEnvironmental ethicsAnimal rightsAnimal welfarePerspective (graphical)CapitalismPoliticsSociologyCentralityPolitical scienceLawEcologyCriminologyBiologyPhilosophy

Abstract

fetched live from OpenAlex

Fashion theorists have largely ignored ethical concerns about the industry's exploitation of nonhuman animals. While critical theory and political economy approaches stress the centrality of animal exploitation to global capitalism, an animal rights perspective critiques the fashion industry's use of nonhuman animals as a 'theatre of cruelty' which turns them from living beings to mere products, or raw materials. Adopting these perspectives, the article provides a brief survey of some key issues, and examines the resurgence of fur sales and fur industry rhetorics. The evidence and the arguments presented illustrate why a critical approach to ethical issues in fashion and beauty cannot exclude nonhuman animals.

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)0.006
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.065
Scholarly communication0.0060.005
Open science0.0000.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.165
GPT teacher head0.426
Teacher spread0.261 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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