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Record W4404800208 · doi:10.51427/cet.sdc.2024.3.3.4

Arquivar e reativar o teatro-música português

2024· article· pt· W4404800208 on OpenAlexfundno aff
Filipa Magalhães

Bibliographic record

VenueSinais de Cena · 2024
Typearticle
Languagept
FieldPsychology
TopicHistorical and Modern Theater Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

As produções pertencentes ao género performativo de teatro-música em Portugal e compostas a partir de 1970 apresentam inúmeros desafios no que respeita à sua preservação, especialmente no contexto do arquivo. Parte da documentação de teatro-música encontra-se dispersa entre várias instituições e acervos pessoais. Estas obras baseiam-se em linguagens idiossincráticas e em práticas performativas não-convencionais, que é preciso identificar e sistematizar. Muitas vezes, é necessário recorrer aos agentes envolvidos nessas performances (compositores, performers, encenadores, técnicos de som, light designers, entre outros) para, por um lado, entender aspetos da performance intrínsecos ao processo de criação, os quais não se conseguem descortinar apenas a partir da documentação, e para, por outro lado, compreender as relações entre a documentação existente. Este é o grande desafio que se coloca atualmente aos musicólogos e arquivistas, e só a partir de um trabalho de colaboração entre estas duas áreas do conhecimento será possível arquivar e reativar o teatro-música. Neste artigo, proponho discutir os conceitos de performance e re-performance, na perspetiva de Diana Taylor, para entender a exequibilidade de salvaguardar a performance no arquivo digital.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.007

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 head0.031
GPT teacher head0.330
Teacher spread0.299 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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