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Record W4392643322 · doi:10.1080/13662716.2024.2328002

Hampered by creation: the unintended consequences of COVID-19 policies on creative firms

2024· article· en· W4392643322 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

VenueIndustry and Innovation · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsNational Circus SchoolToronto Metropolitan University
Fundersnot available
KeywordsBusinessCoronavirus disease 2019 (COVID-19)Government (linguistics)Unintended consequencesWork (physics)RevenueEntertainmentPandemicAmbidexteritySubsidyMarketingCreative industriesPublic relationsEconomicsMarket economyPolitical scienceFinanceKnowledge management

Abstract

fetched live from OpenAlex

The COVID-19 pandemic abruptly interrupted operations for many industries, but in particular the live entertainment sector that was effectively forced into a global shutdown. In response, governments swooped in to keep these organisations afloat by introducing policies aimed at compensating for lost revenues and supporting other forms of activity such as creation. While these reactive measures undoubtedly provided timely and vital relief for some, this study suggests that they also induced important distortions over time. Based on interviews with circus arts managers, the results show that these policies unintendedly introduced or contributed to four main ‘asymmetries’ – outlets, customer base, structure, and talent – that now hamper creative organisations as they transition out of the pandemic. This study contributes to the emerging body of work on the unforeseen consequences of COVID-related support measures, challenges the dominant contextual approach to managing ambidexterity, and provides valuable insights for government and policy actors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.101
GPT teacher head0.375
Teacher spread0.274 · 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