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Record W7111780263

Negotiating Opera : Discursive Representations, Democratic Accessibility and Social Media Branding

2025· book· en· W7111780263 on OpenAlexfundno aff

Bibliographic record

VenueDoria (University of Helsinki) · 2025
Typebook
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
FundersTurun YliopistoUniversity of CambridgeSvenska Litteratursällskapet i FinlandYork University
KeywordsOperaNegotiationMeaning (existential)Construct (python library)PhenomenonIdentity (music)DemocratizationNational identityItalian opera
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines opera as a discursive cultural and social phenomenon, constructed not only within theatrical spaces but also in production practices and public discussions that extend beyond a music-theatrical performance. Focusing on discussions of opera in the media landscape of the early 21st century as related to the democratization challenges around an art form traditionally understood as high and elitist, this approach brings novel perspectives to the relationship between opera and society. More specifically, negotiating opera encompasses the idea that opera is a discursive construct that is subject to continuous negotiations in which meanings and values are produced and reproduced. The aim of this thesis is to (i) identify and examine perceptions of opera in contemporary society and (ii) understand how these perceptions are formed and how they relate to wider cultural trends. This aim leads to two main research questions: “What kind of perceptions of opera as a cultural phenomenon are construed on public discussion arenas, such as newspapers and social media, and in official public communications of opera institutions, in Nordic welfare societies?”, and “How do digitalization and changes in cultural production, including the media landscape, influence the perceived meaning and value of opera in contemporary society?”. These processes are studied in three sub-studies: 1) Discursive media representations of Finnish National Opera during the management crisis of 2007–2009, 2) Accessibility to opera in the digital age among Swedish-speaking Finns, and 3) Branding of Nordic opera companies on Instagram. Theoretically, the study examines opera as a social construct in relation to taste and cultural hierarchies, digitalization and democratization, and commercialization and neoliberalism. Using discourse analysis as the main method, the study analyzes representations of opera in print as well as digital media and in operatic practices in the context of Nordic welfare societies of the 21st century. The first article shows that while the media discourses around the Finnish National Opera seem diverse, they actually restrict the debate to four perspectives – business, arts, elitism, and democracy. These discourses frame also broader discussions about the role of national cultural institutions in society. The second article shows that while digital technology has made opera more accessible in some respects, it has not fundamentally altered the perception of opera as an elite art form. Thus, opera remains a privilege rather than a democratically accessible right. The third article demonstrates that although social media platforms provide opportunities for opera companies to broaden their reach and appeal to new audiences, they also continue to uphold opera’s reputation as an exclusive art form. In conclusion, the study highlights the tension between opera as high culture and opera as accessible. It proposes that it is not the value judgment that is made accessible, but rather the idea of high culture. In light of this study, it can be argued that opera serves as a discursive stage where wider social debates are performed.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.124
Threshold uncertainty score1.000

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 studies0.0020.001
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 head0.038
GPT teacher head0.281
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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