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Record W2160646336 · doi:10.1145/2617995.2617996

Choreography as Mediated through Compositional Tools for Movement

2014· article· en· W2160646336 on OpenAlexaff
Sarah Fdili Alaoui, Kristin Carlson, Thecla Schiphorst

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChoreographyComputer scienceRepresentation (politics)Variety (cybernetics)Movement (music)Process (computing)Expression (computer science)Feature (linguistics)Experiential learningHuman–computer interactionReflection (computer programming)DanceArtificial intelligenceVisual artsProgramming languageAestheticsLinguisticsArtSociology

Abstract

fetched live from OpenAlex

Choreography is the art of crafting movement, developed through a long history of techniques. Like other compositional processes, choreography is a complex creative process that explores a variety of formal procedures that can result in unique artistic creations. Current computational systems for assisting choreography tend to be idiosyncratic, with emphasis on different feature sets of the compositional process (including movement, structure or expression). In this paper we examine existing technological systems for supporting choreography and group them by their purpose: reflection, generation, real-time interaction, and annotation. We then analyze these system features using Laban Movement Analysis, a comprehensive language for movement description, representation, expression and performance. Our paper articulates the relative benefits of these systems based on experiential aspects of choreography, and posits future directions of intelligent systems for supporting and partnering with choreography.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.009
Scholarly communication0.0050.005
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.015
GPT teacher head0.230
Teacher spread0.214 · 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 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

Citations39
Published2014
Admission routes1
Has abstractyes

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Same topicHuman Motion and AnimationFrench-language works237,207