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Record W4413442413 · doi:10.1080/14682761.2025.2546215

Feeling together: the affective project of co-presence and the limits of the audience community

2025· article· en· W4413442413 on OpenAlexafffund
Kelsey Jacobson, Bethany Schaufler-Biback

Bibliographic record

VenueStudies in Theatre and Performance · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsUniversity of TorontoQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaFederation for the Humanities and Social Sciences
KeywordsFeelingPsychologyAestheticsSocial psychologySociologyArt

Abstract

fetched live from OpenAlex

News headlines post-pandemic question whether audience members have ‘forgotten how to behave’ amidst incidents of disruption to theatre performances, suggesting audience norms are in a time of renegotiation and expectations of what it means to be co-present are shifting. This article uses qualitative audience data solicited from spectators attending live, in-person performances in 2021 and 2022 to examine how audiences conceive of, value, and cultivate collective experiences. Data suggest that affect is a strong motivator for audiences to attend co-present performance experiences, and that audiences are motivated to anticipate and enact affective projects in which feelings are circulated amongst a collective who may perceive themselves to feel together. These affective projects, however, are bound up in hegemonic norms that, while they may be pleasurable to some, also replicate exclusionary harms and are therefore in need of close examination and re-evaluation alongside larger reforms to the normative theatre audience experience.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.035
Scholarly communication0.0120.009
Open science0.0010.015
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.061
GPT teacher head0.324
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes2
Has abstractyes

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