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Record W6989539199

Between repetition and variation: a musical performance of malÃcia in capoeira

2017· article· en· W6989539199 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMusicalRepetition (rhetorical device)Musical formVariation (astronomy)Movement (music)Groove (engineering)Action (physics)Adversary
DOInot available

Abstract

fetched live from OpenAlex

The physical expression of Brazilian capoeira features an intriguing combination of playfulness and aggression that practitioners navigate with malícia-the ability to be deceptive.Expressions of malícia in capoeira include attitudes, utterances or actions devised to confuse, distract or mislead the opponent and onlookers, resulting in an improvement of one's position during the physical game.This article explores musical structures connected to malícia and argues that in promoting competition between those engaged in the physical game, musicians bring malícia to the foreground of the musical domain.Because capoeira's music is groove based and patterned at all levels of structure, this study uses periodicity and variation as the main categories of analysis, focusing on how musicians, singers and those playing the physical game manipulate or relate to patterns, variations and tempo at different levels of structure in order to display malícia.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.288
Teacher spread0.259 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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