Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".