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Record W4362519365 · doi:10.24908/iqurcp16320

Revelations: Theatre That Celebrates the End of the World

2023· article· en· W4362519365 on OpenAlexaffvenueabout
Charlotte Dorey

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2023
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGriffinCitizen journalismMedia studiesValue (mathematics)SociologyArt historyHistoryVisual artsArtPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This poster will focus on the participatory play Revelations by Toronto-based theatre creators Anahita Dehbonehie, Griffin McInnes and Aidan Morishita-Miki presented as part of Kingston’s Kick & Push Festival in the summer of 2020. The show used game mechanics to have us prepare for the apocalypse- but not the one we were living in the height of the COVID-19 pandemic, but the potential future nuclear apocalypse. The first half of the show involves the audience communicating with the other groups who are all isolated in their own households via walkie-talkie. The audience then came together in a park downtown to determine who would win the game and “survive” the apocalypse by escaping via boat, car, or on foot (ultimately decided by the roll of dice).
 At its core, this show asked what we value more, the individual or the collective. This is a piece of participatory theatre and participation is, by definition, not something you can do alone. And yet when we look at the inspiration for this show we see so much individualism. Doomsday preppers create bunkers for themselves and their loved ones, preparing for the day when a natural disaster, economic collapse, or nuclear war means that it’s everyone for themselves. In its sim, Revelations asks us to confront our own approach to the end of the world; it offers us valuable lessons in collective care that can be applied easily to our real world.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.241
GPT teacher head0.420
Teacher spread0.179 · 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 designTheoretical or conceptual
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
Published2023
Admission routes3
Has abstractyes

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