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Record W4399141622 · doi:10.46787/jcbp.v3i1.3845

Participation as Intimate Act: Audience Reflections on Strategies of Consent in Roll Models

2024· article· en· W4399141622 on OpenAlexaff
Kelsey Jacobson, Bethany Schaufler-Biback

Bibliographic record

VenueJournal of Consent-Based Performance · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsUniversity of TorontoQueen's University
Fundersnot available
KeywordsPsychologyPolitical scienceSocial psychologyInternet privacySociologyPublic relationsComputer science

Abstract

fetched live from OpenAlex

Immersive, interactive, and participatory performances often promise co-creative or otherwise unique roles for spectators, who may be called upon to directly interact with performers, explore performance sites, or help shape plot. The nature of much of this heightened participation is important to note: audience members might be expected to be visible onstage, make choices that affect the show, offer personal information, or engage directly with actors, in an ask for labor that is resultantly accompanied by increased risk, vulnerability, and relationality. This article uses the case study of Roll Models, a longform improv show that enacts a short adventure campaign in the style of Dungeons & Dragons on stage, in order to characterize audience participation as an intimate act. Building on previous scholarship aimed at assessing consent, intimacy, and participation in immersive theatre and live action role-play (Villarreal 2021, Biggin 2017, Machon 2013), we query not only into what participation, consent, and on-boarding processes were present in the performance, but also how audience members themselves viewed such mechanisms, understood and learned their role in the performance, and related to actors and each other.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.122
GPT teacher head0.437
Teacher spread0.315 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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