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Record W2809913889 · doi:10.18061/emr.v12i3-4.5814

Tapping to Carter: Mensural Determinacy in Complex Rhythmic Sequences

2018· article· en· W2809913889 on OpenAlexaff
Poudrier

Bibliographic record

VenueEmpirical Musicology Review · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTappingRhythmBeat (acoustics)PianoDeterminacySalience (neuroscience)PsychologyCognitive psychologyMusicalFinger tappingCommunicationMathematicsAudiologyArtAcoustics

Abstract

fetched live from OpenAlex

The tapping paradigm has played an important role in formulating beat induction models. However, experimental studies that make use of actual music as source materials to investigate pulse finding mechanisms in complex rhythmic sequences are lacking. The present study proposes to use the concept of mensural determinacy, that is, the emergence of temporal expectations that may or may not be realized (Hasty, 1997), to explore the relative salience of an implied beat in two contrasting rhythmic sequences extracted from Elliott Carter's 90+ for piano (1994), and test the influence of style-specific expertise on listeners' spontaneous tapping performance. The results of the experiment were consistent with the hypothesis that familiarity with the style represented by the source materials contributes to a more stable tapping period. In addition, although accent was found to have a main effect on tapping behavior, it also interacted with global temporal structure and a number of musical parameters and participant characteristics, including gender. Exploratory analyses of several additional musical parameters and participants' characteristics are also suggestive of how experimental methods could be complemented by post-hoc score analysis to investigate the contributions of specific factors to the relative influence of first- and second-order periodicity on musicians' beat percepts.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.999

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)0.0010.001

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 head0.227
GPT teacher head0.430
Teacher spread0.203 · 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.

Study designNot applicable
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

Citations7
Published2018
Admission routes1
Has abstractyes

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