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Record W2784045479 · doi:10.3138/ctr.173.002

<i>BRANTWOOD:</i> Canada’s Largest Experiment in Immersive Theatre

2018· article· en· W2784045479 on OpenAlexvenueaboutno aff
Julie Tepperman, Mitchell Cushman

Bibliographic record

VenueCanadian Theatre Review · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMusicalPerforming artsThe ImaginaryVisual artsArtCharacter (mathematics)Performance artDramaArt historyMedia studiesSociologyPsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

Julie Tepperman and Mitchell Cushman, co-creators, playwrights, and directors of Brantwood, write about the process of creating the largest site-specific immersive musical in Canada. Originally commissioned by Associate Dean Michael Rubinoff and Sheridan College’s Musical Theatre Program, Brantwood was designed for and performed in a 90-year-old school in Oakville, Ontario that had been closed down due to low enrolment. The piece consisted of 40 original songs (composed by Anika Johnson, Britta Johnson, and Bram Gielen) imbedded in 11 one-hour scripted storylines, each set during a different decade in the history of this imaginary high school. The 15 hours of total material unfolded simultaneously over the course of each three-hour performance, and the audience had free rein to roam everywhere in the building and to follow whichever character they chose in the 42 person cast. Julie and Mitchell write about the challenges of creating theatre on such a large scale, and immersing the audience in an environment that gives them freedom to roam and explore, and engage with the show in both direct and indirect ways, and to push the boundaries of intimacy between performer and audience.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.996

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)0.0050.000

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 head0.020
GPT teacher head0.230
Teacher spread0.211 · 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.

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

Citations4
Published2018
Admission routes2
Has abstractyes

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