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Enregistrement W2586551189

An Ecological Analysis of Music Making in Ensemble Rehearsals

2007· article· en· W2586551189 sur OpenAlexaboutno aff
Linda T. Kaastra

Notice bibliographique

RevueeScholarship (California Digital Library) · 2007
Typearticle
Langueen
DomaineComputer Science
ThématiqueMusic Technology and Sound Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGestureContext (archaeology)MusicalComputer scienceRepresentation (politics)PsychologyHuman–computer interactionZoomCommunicationCognitive psychologyCognitive scienceVisual artsArtificial intelligence
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

An Ecological Analysis of Music Making in Ensemble Rehearsals Linda T. Kaastra, (eudaimonia96@gmail.com) Individual Interdisciplinary Graduate Studies Program, University of British Columbia Keywords: musical interaction, music gesture, performance analysis. A representation like the above allows the analyst to zoom in on single events while maintaining an awareness of context. Introduction Coordination Devices This poster presents a method for conceptualizing domains of activity in “real world” music making. An extension of Herbert H. Clark’s (1996) “action” theory of language use, this poster demonstrates how music making can be viewed as an integrated layering of verbal and nonverbal activity, personal and public goals, and situational awareness. A sample ecological analysis of performed music drawn from real world rehearsal data demonstrates how single parameters of performance, e.g. gesture, can be understood as one of a number of coordination devices used in the process of negotiating musical understanding. Clark provides the following representation for identifying coordination devices: For two people, A and B, it is common ground that p if and only if: 1. A and B have some information that some basis b holds; 2. b indicates to A and B that A and B have information that b holds; 3. b indicates to A and B that p. This poster provides several variables for p and b to demonstrate the layering of coordination devices (e.g. score markings, body motions, performance conventions) in the Takemitsu rehearsal data. Event Structure in Rehearsal Clark discusses music making as a single activity such as “playing a duet” or “playing a string quartet.” He suggests that such musical activities are periodic, “synchronized mainly by a cadence or rhythm” (p. 82), whereas day to day activities such as “shaking hands, eating dinner, waving good-bye,” are largely aperiodic. Clark also defines musical activities as balanced; even though he acknowledges that one member of an ensemble can initiate an activity, he feels that once the performance begins, the participants engage as equals. This analysis presents a picture of musical activity that is alternately periodic and aperiodic, balanced, and unbalanced. Real World Rehearsal Data Data for this study includes video-taped recordings of nine rehearsals and one performance of a single ensemble preparing Toru Takemitsu’s Masque for Two Flutes. Data was collected according to the guidelines of grounded theory. The flutists consented to have all rehearsals of this piece recorded and to have their discussion and repetition analyzed. Sessions are labeled by date (e.g. 92905 is September 29, 2005). Finally, a preliminary analysis highlights how conventions of performance such as, “being visible with [x],” (where x could be drawn from any of the following: Intent for: breath, beat, articulation, dynamics, character) can be used to distinguish between autonomous and participatory actions (Clark p. 61). Ensemble A-and-B is doing joint action k if and only if: 0. the action k includes 1 and 2; 1. A intends to be doing A’s part of k and believes that 0. 2. B intends to be doing B’s part of k and believes that 0. In this case, both flutists intend to participate together and to “be visible” with their intentions in order to facilitate coordination. Findings To isolate activities within the rehearsal process, I borrow Clark’s representation for identifying sections and boundaries: Rather than fulfilling static measurable roles in music making, coordination devices shift in emphasis as the flutists become more familiar with the music. In the first phase, considerable emphasis is placed on the beat markings added to the score. Later, body motion is emphasized as a coordination device. Later still, the use of body motion appears expendable as the flutists respond to experimental changes in the performance environment. Acknowledgments: The author would like to thank Dr. Brian Fisher, Dr. Eric Vatikiotis-Bateson and the National Sciences and Engineering Research Council of Canada for assistance with this project. Entry: A and B go from not being in J to being in J Body: A and B are in J Exit: A and B go from being in J to not being in J Entries and exits have to be engineered for each joint activity (p. 36). References: Clark, H. H. (1996). Using language. Cambridge: Cambridge University Press.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil0,049

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,023
Tête enseignante GPT0,253
Écart entre enseignants0,230 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

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