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Expor a arte da performance

2016· article· pt· W2599507687 on OpenAlexaff
Anne Bénichou

Bibliographic record

VenueMuseologia & Interdisciplinaridade · 2016
Typearticle
Languagept
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Alguns anos após a publicação de uma primeira História “Geral” da Arte da Performance em 1988, Performance Art: From Futurism to the Present de RoseLee Goldberg, várias instituições museais organizaram exposições de grande importância consagradas às obras performativas de um passado recente ou mais remoto, provenientes dos centros hegemônicos, mas também locais ou periféricos. Isto porque a arte da performance desenvolveu-­se em resistência às histórias hegemônicas da arte e às suas instituições, porque suas obras são efêmeras, porque elas envolvem o corpo, porque dependem do “vivo” e do “direto”, e as instituições curatoriais deparam-se com certas dificuldades e paradoxos. Elas não podem fazer a economia de uma reflexão de natureza historiográfica que questione as categorias, os métodos, os conceitos, os lugares, as fontes, as genealogias e as narrativas da história da arte. Por conseguinte, as questões levantadas são: uma reflexão de natureza historiográfica pode ser realizada no âmbito de uma exposição sobre a arte da performance? É da responsabilidade dos curadores? Que papel os artistas podem ter nesta fábrica das representações históricas? Observa­-se uma reconfiguração da divisão das responsabilidades entre os historiadores e os teóricos da arte, os curadores de exposição e os artistas? A análise de quatro exposições recentes permite identificar tantas figuras experimentais que renovam de acordo com estratégias singulares, as maneiras de escrever as histórias da arte: a hipermídia, a heterotopia, o repertório e a paralaxe.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.017
Scholarly communication0.0130.009
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0260.005

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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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 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
Published2016
Admission routes1
Has abstractyes

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