Bibliographic record
Abstract
Abstract The article focuses on some of the more important developments that have affected the American musical over the years. The amount of money needed to produce a musical has increased since the onset of the depression, but especially since the 1960s. The cost of production, coupled with the introduction of several cheaper, more widely accessible entertainment forms, has forced the musical to struggle financially and aesthetically at various periods during the postwar era. Periods of high inflation, such as during the 1930s, affected the criteria for hit status, for example shows had to run for longer stretches to be profitable. The marketing for the show at that time was particularly intense, and the spectacle aspect was strongly promoted by producer Garth Drabinsky, under the auspices of his Canadian production company, Livent. The longer average runs of Broadway musicals depended in part on an increasingly international audience, which was seen as transitory and ever renewing. Since the advent of rock, amplification has become increasingly common and this was for several reasons. Many actors needed microphones to protect their voices and to be heard above the electric instruments that accompanied them. Film and sound recording technologies exerted significant influence on the stage musical and advances in sound design have allowed theatrical productions to offer cleaner, more balanced sound from the orchestra pit and stage.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".