The Dialogue of Giants: How Broadway and Hollywood “Saved” American Animation (and Were Saved in Return). (Kunze, Peter C. Staging a Comeback: Broadway, Hollywood, and the Disney Renaissance. New Brunswick, NJ: Rutgers University Press, 2023. 224 р.)
Bibliographic record
Abstract
Peter Kunze’s book Staging a Comeback: Broadway, Hollywood, and the Disney Renaissance is a (overwhelmingly) well-researched study of the transmedial migration of popular narratives in the 1980s and the 1990s. Focused on Disney’s appropriation of the Broadway integrated musical (H. Ashman, A. Menken), the study demonstrates how the musical theatre conventions improved the quality of Disney’s main product — the animated film. Kunze engages in close reading of an extended episode from the history of cultural production (the Disney Renaissance), showing the complexity and unpredictability of various media convergences. For instance, the book reconfigures the roles of managerial and creative labourers behind the Disney transformation, wittily (and convincingly) bringing to the forefront 1982 as annus mirabilis, which triggered immense changes in the cultural sector. After discussing Disney's appropriation of the musical Broadway, the book reveals how the updated animated musical comes back to the theatrical stage and transforms ‘respectable’ Broadway by alternative styles and agendas (Julie Taymor’s The Lion King). Apart from other sources, the research uses hardto- access archival materials, the author's interviews with the practitioners and their entourage.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".