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Record W2979520337 · doi:10.1017/s026114301900028x

Good things come in threes: triplet flow in recent hip-hop music

2019· article· en· W2979520337 on OpenAlex
Ben Duinker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePopular Music · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsPopularitySalientBlueprintRhetorical questionStyle (visual arts)AestheticsSociologyLiteratureArtPsychologyVisual artsPolitical scienceLawSocial psychology

Abstract

fetched live from OpenAlex

Abstract MCs (rappers) such as Cardi B, Kendrick Lamar, Drake, Big Sean and Young Thug use triplet rhythms in their rapping, a practice that is known as triplet flow. This paper argues that the prevalence of triplet flow is one of the most aurally salient features of contemporary hip hop, and exemplifies the popularity and influence of the Atlanta-centred genre of trap music through its sparse, slow beats. Three types of triplet flow are defined – mixed, phrasal and total – and are used to explore how various songs and artists active in the late 1980s and early 1990s provided the stylistic blueprint for triplet flow's recent explosion in popularity. With the aid of a 50 song mini-corpus, the paper concludes with a general survey of stylistic characteristics common in many songs featuring triplet flow, and further analysis of two of these songs in order to illuminate the creative, rhetorical and virtuosic potential that underpins this ostensibly simple style of rapping.

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.

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 categoriesInsufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.001

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 head0.041
GPT teacher head0.211
Teacher spread0.170 · 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