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Record W2292926924 · doi:10.14288/1.0071678

The impact of "The Met : Live in HD" on local opera attendance

2011· article· en· W2292926924 on OpenAlexaboutno aff
Stephan van Eeden

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsOperaAttendanceArtPolitical scienceVisual arts

Abstract

fetched live from OpenAlex

Live-streamed movie theatre broadcasts are a new phenomenon in opera. In 2006-2007, the Metropolitan Opera in New York began transmitting select live Met performances into cinemas across Canada, the U.S. and Europe. The program was entitled The Met: Live in HD and since its inception, has expanded in audience reach, content and mandate. Many local live opera companies speculate that Live in HD is a threat to their business. This study identifies and assesses the impact of The Met: Live in HD on local opera attendance. A survey was conducted in a major North American city with a resident midsize professional opera company and a midsize amateur opera company. We surveyed HD-attendees at Live in HD performances as well as at amateur and professional live opera performances. The study investigates whether Live in HD actually exposes new audiences to opera, how attendees compare HD and live opera, and whether viewers are more likely to see a live local production or simply more likely to view another broadcast. The results show that Live in HD does not at present cannibalize the local live opera audience, but it does establish an audience for itself. Live in HD is not viewed as an inferior product to live opera. There is evidence that the program is so successful that it builds a loyal following –audiences attend because they enjoy the experience, some decide to subscribe, others begin to prefer the format. Live in HD attendees are very likely to reattend HD but not necessarily live opera. There is no evidence that Live in HD generates more live opera attendance or brings new audiences into local opera houses.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.381

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 studies0.0000.001
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 head0.220
Teacher spread0.192 · 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 designObservational
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

Citations6
Published2011
Admission routes1
Has abstractyes

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