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Record W4240426888 · doi:10.38055/fs030107

#NaturalDye

2020· article· en· W4240426888 on OpenAlexvenueno aff
Kelsie Doty, Denise Nicole Green, Dehanza Rogers

Bibliographic record

VenueFashion Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsCraftNatural (archaeology)Articulation (sociology)Visual artsSocial mediaTextileSociologySituatedSpace (punctuation)Style (visual arts)ArtComputer scienceHistoryPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Natural dyes from plants, insects, and fungi can be used to color yarns and textiles by craftspeople. Craft communities interested in natural dyes are using social media platforms such as Instagram to connect and share knowledge and to generate commerce for their products. #Naturaldye is a documentary film that explores the use of Instagram as a pedagogical, social, commercial, and creative space where dyers foster community and support businesses. Participants in the film discuss what types of information they find essential to articulate while also describing themselves as part of a community of other makers and artists. Theoretically, #Naturaldye is situated at the intersection of the circuit of style-fashion-dress (Kaiser, 2012) and imagined communities (Anderson, 1983). Social media platforms like Instagram enable articulation between fashion, textiles, commerce, and craftspeople where knowledge of natural dyes, dyers, and their work is conveyed to a wider array of individuals that become part of an imagined community through craft.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6240.273

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 head0.213
GPT teacher head0.300
Teacher spread0.086 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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