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Enregistrement W1984414984 · doi:10.1353/tt.2014.0041

Dancing Performance Generating Systems

2014· article· en· W1984414984 sur OpenAlexaboutno aff
Pil Hansen

Notice bibliographique

RevueTheatre topics · 2014
Typearticle
Langueen
DomainePsychology
ThématiqueDiversity and Impact of Dance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDanceRest (music)Visual artsArtTransition (genetics)Medicine

Résumé

récupéré en direct d'OpenAlex

Dancing Performance Generating Systems Pil Hansen (bio) This article invites you on a simple, experiential journey into the complex mystery of dance works that systematically generate performance onstage. This praxis is situated in a lineage of task-based creation; it is brought to life through descriptions of two works by internationally recognized choreographers from Canada; and it is examined through a dramaturgical lens with the aim of revealing how the systems work and are danced.1 Touch Me Two dancers undress and, not quite naked, they seek eye contact and approach each other. At close proximity, they each retract into solo dances of twisting joints, reflexes, and muscle contractions. I remember Michael Caldwell rubbing his wrist against his shoulder blades while his chin tugs at his collar bone and his knees let go; not quite interlocked, Stephanie Tremblay Abubo stretches her face and arms away and apart. Both dancers are caught in looping repetitions of the solo dances until his or her hand rests upon the other's body, allowing the touching dancer to relax for the duration of the contact. Multiple cycles of these looped solos and moments of rest continuously shift the alignment of movements. The cycles come to a momentary halt when the dancers find each other's hands and cautiously begin to walk together, in transition. This fragile union soon splits into another cycle of retracted solos and rest, and the full series of cycles and shared transition continues to unfold and evolve. In my memory of this section of Crave (2013), I am watching from a chair next to the choreographer Karen Kaeja2 and I am facilitating her development of the piece as her dramaturg. My focus is on the dancers' choices of when to touch each other and their implicit (mis)alignment of tempo, muscle tension, and movement. Each stage of developing, trying out, and adjusting the "rules" of the dancing are alive in my mind, and I am assessing how our last changes affect the dancers' choices differently from previous stages of the work. I am also paying attention to how their choices, in turn, affect me as a spectator: I notice what my attention is drawn towards, sense contractions of and relaxation in my core muscles, and register the competing emotions and associations evoked by the experience. The only layers of meaning that I am concerned with are general themes and the detectable logic of the system that the solos, rules, cycles, and series comprise. Layers of interpretation depend on each viewer's associations to personal memories of intimacy that are inaccessible to me, but will enrich and form large parts of his or her experience. The piece's ability to trigger such associations and feed them into the system through our viewer's perception is what matters. I am sharing this memory because it offers a simple and clear example of how a performance generating system can be created, how it systematically drives the dancers to generate performance onstage, and what kind of invitation it extends to audience members. [End Page 255] Concept I am using the term performance generating system for rule- and task-based dramaturgies that systematically set in motion a self-organizing process of dance generation. When creating such a system, the focus is not on the completion of a choreographic composition of movements, phrases, series, and interactions with fully set muscle intentionality, tempo, and markers of what takes place where and when in space and time. The choreographer and dramaturg are also not creating frames for improvisation of movement that is based on the dancers' impulses. Rather, when creating a performance generating system, the aim is to arrive at a set of shared tasks and rules that both divides and sharpens the performers' attention, while limiting their options and challenging them to make movement decisions in the moment. Fully set choreography or improvised material, like the solos in the Crave example, may be fed into the system and used as resources to be processed by the dancers' choices. However, the central principle of the piece's dramaturgy remains the way in which tasks and rules generate interaction and movement. Touch Rules When creating the described section...

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,851
Score d'incertitude au seuil0,504

Scores Codex et Gemma par catégorie

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

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 Opus0,021
Tête enseignante GPT0,255
Écart entre enseignants0,234 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
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

Citations5
Publié2014
Routes d'admission1
Résumé présentoui

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