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Record W4246127946 · doi:10.7202/1086259ar

Amazonia—Music Theatre in Three Parts: A Transcultural Operatic Experience?

2021· article· fr· W4246127946 on OpenAlexvenueno aff
Vítor Castelões Gama, Marcelo Velloso Garcia

Bibliographic record

VenueIntermédialités Histoire et théorie des arts des lettres et des techniques · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicArts, Culture, and Music Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOperaAestheticsIndigenousPoliticsResistance (ecology)LegitimationTransculturationHistoryVisual artsArtSociologyAnthropologyPolitical science

Abstract

fetched live from OpenAlex

This article discusses Amazonia—Music Theatre in Three Parts ([AMT] 2010), a collaboration between the Yanomami, Brazilian and German producers as a transcultural form of resistance that touches on issues of transculturation and Indigenous peoples’ culture and portrayal. We argue that AMT claimed legitimation as an opera and publicized the Yanomami’s views about what extractivism is doing to our planet: devastation beyond tipping points. We first discuss how the Yanomami had been portrayed in art before this opera, and then turn to how the operatic form of AMT was perceived by its reviewers; finally, we offer a critique of the reviewers’ arguments against labelling AMT as a transcultural opera, as we believe these arguments are mainly political. This article aims to demonstrate the fluidity of the boundaries between opera and musiktheater, and of what characterizes a transcultural experience.

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)0.003
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.011
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.056
GPT teacher head0.324
Teacher spread0.267 · 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
Published2021
Admission routes1
Has abstractyes

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