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Record W3200653021 · doi:10.3389/fcomm.2021.650382

The Language of Gángan, A Yorùbá Talking Drum

2021· article· en· W3200653021 on OpenAlexafffund
Samuel Akinbo

Bibliographic record

VenueFrontiers in Communication · 2021
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsYorubaLinguisticsDrumVowelGrammarPsychologyCommunicationConsonantSpeech recognitionComputer scienceHistory

Abstract

fetched live from OpenAlex

It is widely known that Yorùbá drummers communicate through their native drums. This paper investigates the grammar of gángan, which belongs to a family of Yoruba drums called dùndún. The results of this study show that Yorùbá drummers represent the phonetic realisation of lexical and grammatical tones of their language with the drum. Statistically, the speech tones and the acoustic correlate of the corresponding drum representations have a significant positive relationship. In both spoken and drum communication, vowel (V) and consonant-vowel (CV) prosodic units have different statuses. To conclude, Yorùbá drummers communicate via the gángan drum by transposing certain phonemic features and maybe phonological conditions of their language to musical forms.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.344
Teacher spread0.323 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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