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Record W4415314054 · doi:10.1080/15290824.2025.2500031

Pas de Trois: A Literature Review and Project Audit of Virtual Reality Technology in Dance Pedagogy and Performance

2025· article· en· W4415314054 on OpenAlexaff
Olivia DiGiammarino, Rachel Gorman, Eva Peisachovich, Lora Appel

Bibliographic record

VenueJournal of Dance Education · 2025
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsYork UniversityInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsDanceDance educationVirtual realityAuditTeaching method

Abstract

fetched live from OpenAlex

This literature review discusses themes at the intersection of Virtual Reality (VR) technology and dance. This article explores three themes: VR dance for pedagogy, VR dance as and for performance, and issues of embodiment in VR dance. We argue that real-life dance instructors have been alienated from pedagogical input, and dance instructors are conspicuously absent from the discourse on the future of VR dance training. This article argues that while opportunity for VR performance is growing, it will be important for choreographers and dancers to be engaged in the technology in order for the form to advance technically and aesthetically. Lastly, we explore opportunities for authentic embodiment, access to spaces, and global experiences afforded by VR dance technology. We call for meaningful partnerships between dance creators, users, and VR technologists.

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 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.308
Teacher spread0.298 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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