MétaCan
Menu
Back to cohort
Record W6903317023 · doi:10.1109/tem.2025.3555331

Exploring the Role of Disruptive Periods in the Digital Transformation of Theatre and Performing Arts

2025· article· en· W6903317023 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Engineering Management · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsSociotechnical systemAdaptabilityDigital transformationPerforming artsPsychological resilienceDigital artResilience (materials science)Field (mathematics)Bridge (graph theory)

Abstract

fetched live from OpenAlex

This article investigates the impacts of the disruptive periods of uncertainty and great change caused by processes such as the 2020 global Covid-19 pandemic, on the performing arts industry, with a specific focus on theatre. We use a combination of systematic literature review and semistructured interviews with professionals in the field to explore how the shift to digital platforms has reshaped production, distribution, and consumption within this traditionally live interaction-dependent sector. This article identifies key transformations in the sociotechnical regime of the performing arts, highlighting the accelerated integration of digital technologies and the consequent shifts in audience engagement and economic models. Theoretical contributions of this article include insights into the resilience and adaptability of creative industries in the face of regulatory and environmental changes, while practical implications point to the need for innovative economic strategies and policy support to bridge the digital divide.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.142

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 head0.028
GPT teacher head0.239
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