MétaCan
Menu
Back to cohort
Record W4210663468 · doi:10.5206/tba.v3i1.13907

Artist of Liminality: Miwa Yanagi’s Myth Machines as Heterotopia

2021· article· en· W4210663468 on OpenAlexvenueno aff
Yuma Terada

Bibliographic record

Venuetba Journal of Art Media and Visual Culture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSpatial and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionMythologyHeterotopia (medicine)EnthusiasmPoliticsLiminalitySociologyArt historyVisual artsArtAestheticsLiteratureLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

In February 2020, Miwa Yanagi: Myth Machines (2019-2020), a traveling exhibition of works by the Japanese contemporary artist Miwa Yanagi (1967-), concluded its tour across Japan after failing to incite meaningful critical response from art historians and critics. The year-long, five-museum itinerary of the solo show reflected the public’s keen interest in Yanagi’s first major exhibition in a decade, but the enthusiasm was betrayed by the paucity of scholarly attention; beyond the four essays included in the catalogue, hardly any scholar or critic seriously engaged with the artist who previously represented Japan at the Venice Biennale and whose work continues to be exhibited internationally. The few texts that appeared display a noticeable anxiety toward Myth Machines—in particular its unapologetic juxtaposition of photography and theater—which suggests a failure of the prevailing art historical language to speak and write about Yanagi’s career. In response to this laconic condition, this paper identifies the concept of heterotopia, delineated by Michel Foucault on three occasions between 1966 and 1967, as a useful device to activate a discourse on Yanagi’s exhibition. A reading of Myth Machines as a heterotopia reveals an exhibition that astutely comments on the ongoing global political moment defined by divisions along racial, gender and national boundaries, visually symbolized by former American president Donald Trump’s divisive border wall.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.328

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.340
Teacher spread0.318 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuetba Journal of Art Media and Visual CultureSame topicSpatial and Cultural StudiesFrench-language works237,207