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Record W3216569998 · doi:10.1590/2238-38752016v636

COMO ESTUDAR A EMOÇÃO MUSICAL? PROPOSTAS METODOLÓGICAS A PARTIR DE PESQUISA JUNTO AOS CIGANOS DA TRANSILVÂNIA (ROMÊNIA)

2016· article· pt· W3216569998 on OpenAlexaff
Filippo Bonini Baraldi

Bibliographic record

VenueSociologia & Antropologia · 2016
Typearticle
Languagept
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsMusicalHumanitiesArtSociologyLiterature

Abstract

fetched live from OpenAlex

Resumo Ainda que os etnomusicólogos não ignorem a estreita ligação da música com os processos emocionais, eles deixaram o tema de lado durante quase meio século. É duplo o objetivo deste artigo. Em primeiro lugar, serão analisadas as relações entre emoções e música em um contexto cultural bem delimitado, a saber, aquele de uma comunidade cigana da Transilvânia (Romênia). Adotamos como critério metodológico focar a atenção nos "prantos musicais", situações em que lágrimas e música caminham juntas. Foram analisados três contextos distintos de performance: a prestação de serviço profissional, as festas espontâneas e os funerais. A partir dessas descrições etnográficas, o segundo objetivo consistirá em extrapolar informações que possam ser comparadas com dados provenientes de outras sociedades. No longo prazo, esse procedimento permitirá identificar os processos psicológicos e sociais recorrentes, quiçá universais, da emoção musical.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0020.014
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.070
GPT teacher head0.334
Teacher spread0.263 · 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 designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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