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Record W3080329968 · doi:10.38055/fs010114

A Fashion Exhibit Without Fashion

2018· article· en· W3080329968 on OpenAlexvenueno aff
Jennifer Ayres

Bibliographic record

VenueFashion Studies · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionClothingVisual artsPremiseScholarshipSculptureArtThe artsPerspective (graphical)TextileAestheticsHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this review, I critically examine the fashion and art exhibition “fashion after Fashion,” April 7–Aug 27, 2017 at the Museum of Arts and Design in New York City, curated by Hazel Clark and Ilari Laamanen. The exhibition design was commissioned work by six interdisciplinary artists/designers who incorporated a mix of sculpture, performance, and audiovisual material into their installations. The different installations, taken together and experienced together, acted back and upon each other in interesting ways in the exhibition, which was a strength of the curators’ method; the use of commissions exclusively acted as a kind of artistic method in itself. The first and most notable thing about the exhibit was that there were no clothes on mannequins. While the exhibition’s premise was on fashion, the intentional absence of clothing was a risky strategy the curators pursued to intervene in how viewers think about fashion. The installations were purposely amorphous and abstract as well to inspire a broader consideration of what fashion can be and what bodies can do. Though the relationship between fashion and the body has been a constant topic in fashion scholarship, this exhibition offered a new perspective through commissioning and showcasing the category-defying work of recent fashion and art school graduates and performance artists.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.004

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 head0.100
GPT teacher head0.313
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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