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Record W7155195237 · doi:10.7202/1124298ar

Conference Report : AAWM Special Topics Symposium 2023. Theoretical, Analytical, and Cognitive Approaches to Rhythm and Meter in World Musics

2025· article· en· W7155195237 on OpenAlexvenueno aff
Tiffany Nicely

Bibliographic record

VenueRevue musicale OICRM · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalityDocumentationMusicologySession (web analytics)Panel discussionFourth WorldCognitionMusic theory

Abstract

fetched live from OpenAlex

The study of temporality in world musics raises several questions regarding how music is organized and perceived. The proliferation of theories and points of view to arise in the past two decades attests to the importance of and interest in topics related to this field. The Analytical Approaches to World Musics Special Topics Symposium on Theoretical, Analytical, and Cognitive Approaches to Rhythm and Meter in World Musics brought together forty scholars with fresh approaches to this field. This online conference took place over four days in June 2023. Co-chaired by Lina Tabak and the author of this report, the symposium featured six paper sessions, a special session planned by the organizing committee, a panel discussion organized by the program committee, a book dialogue, and a keynote by Daniel Avorgbedor. Presenters affiliated with six continents took part. The symposium was co-sponsored by the Analytical Approaches to World Musics Journal , the CUNY Graduate Center, the Barry S. Brook Center for Music Research and Documentation (CUNY), and the International Foundation for the Theory and Analysis of World Musics (IFTAWM).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

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

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 head0.106
GPT teacher head0.294
Teacher spread0.187 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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