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Record W3032959170 · doi:10.1215/22011919-8142220

Fermenting Feminism as Methodology and Metaphor

2020· article· en· W3032959170 on OpenAlexaff
Lauren Fournier

Bibliographic record

VenueEnvironmental Humanities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMetaphorFeminismSociologyFermentationGender studiesPhilosophyBiologyLinguistics

Abstract

fetched live from OpenAlex

Abstract This article proposes the possibilities of fermentation, or microbial transformation, as a material practice and speculative metaphor through which to approach today’s transnational feminisms. The author approaches this from the perspective of their multiyear curatorial experiment Fermenting Feminism, looking to multidisciplinary practices across the arts that bring together fermentation and feminism in dynamic ways. The article outlines ten ways in which fermentation is a ripe framework for approaching transinclusive, antiracist, countercolonial feminisms. As the author takes up these points, drawing from scholarly and artistic references alongside lived experience, they theorize the ways fermentation taps into the fizzy currents within critical and creative feminist practices. With its explosive, multisensory, and multispecies resonances fermentation becomes a provocation for contemporary transnational feminisms. Is feminism, with its etymological roots in the feminine, something worth preserving? In what ways might it be preserved, and in what ways might it be transformed? The author proposes that fermentation is a generative metaphor, a material practice, and a microbiological process through which feminisms might be reenergized—through symbiotic cultures of feminisms, fermentation prompts fizzy change with the simultaneity of preservation and transformation, futurity and decay.

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)0.010
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.994
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.056
Scholarly communication0.0080.008
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.123
GPT teacher head0.332
Teacher spread0.209 · 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.

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

Citations69
Published2020
Admission routes1
Has abstractyes

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