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Record W2753140505 · doi:10.14236/ewic/eva2017.37

A Framework for Hybrid Multimodal Performances

2017· article· en· W2753140505 on OpenAlex
Shannon Cuykendall, prOphecy sun, Reese Muntean, Thecla Schiphorst, Steve DiPaola

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueElectronic workshops in computing · 2017
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHuman–computer interactionComputer sciencePerforming artsVirtual realitySpace (punctuation)Wearable computerMultimediaRelation (database)Action (physics)Physical spaceVirtual spaceArtificial intelligenceVisual artsArt

Abstract

fetched live from OpenAlex

The boundaries between physical and virtual spaces are becoming more blurred in our everyday lives with the advent of wearable action cameras, virtual reality technologies, and algorithmicallyled audience interactions. Artists and creatives have been at the forefront of exploring these new technologies; however, little literature exists that reflects on best practices for navigating this new complex space. We reflect on our experiences in creating and participating in what we refer to as ‘hybrid multimodal performances’ or performances that blend physical and virtual spaces. We propose a framework of aesthetic choices we have implemented to seamlessly blend physical and virtual entities. We consider aspects such as the interaction between the camera and performer, the integration of multiple conceptual spaces, the changing relation between the artist and the work, and the multiple transformations of shape that occur when transitioning between physical and virtual spaces.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.344
Teacher spread0.320 · 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