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Record W2095018050 · doi:10.1525/mp.2009.26.4.335

Music and Motion—How Music-Related Ancillary Body Movements Contribute to the Experience of Music

2009· article· en· W2095018050 on OpenAlexaff
Manfred Nusseck, Marcelo M. Wanderley

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsMotion (physics)Movement (music)Embodied cognitionPsychologyTorsoPerceptionMusicalKinematicsCommunicationMotion captureGestureCognitive psychologyPerforming artsMusic perceptionDynamics (music)Body postureComputer scienceArtificial intelligencePhysical medicine and rehabilitationAestheticsArtVisual artsNeuroscience

Abstract

fetched live from OpenAlex

EXPRESSIVE PERFORMER MOVEMENTS IN MUSICAL performances represent implied levels of communication and can contain certain characteristics and meanings of embodied human expressivity. This study investigated the contribution of ancillary body movements on the perception of musical performances. Using kinematic displays of four clarinetists, perceptual experiments were conducted in which participants were asked to rate specific music-related dimensions of the performance and the performer. Additionally, motions of particular body parts, such as movements of the arms and torso, as well as motion amplitudes of the whole body were manipulated in the kinematic display. It was found that manipulations of arm and torso movements have fewer effects on the observers' ratings of the musicians than manipulations concerning the movement of the whole body. The results suggest that the multimodal experience of musicians is less dependent on the players' particular body motion behaviors than it is on the players' overall relative motion characteristics.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.317
Teacher spread0.275 · 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 designObservational
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

Citations102
Published2009
Admission routes1
Has abstractyes

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