Bibliographic record
Abstract
In this expansive project, Nancy Yunhwa Rao examines the world of Chinatown theaters, focusing on iconic theaters in San Francisco and New York but also tracing the transnational networks and migration routes connecting theaters and performers in China, Canada, and even Cuba. Drawing on a wealth of physical, documentary, and anecdotal evidence, Rao brings together the threads of an enormously complex story: on one hand, the elements outside the theaters, including U.S. government policies regulating Chinese immigration, dissemination through recordings and print materials of the music performed in the theaters, impresarios competing with each other for performers and audiences, and the role of Chinese American business organizations in facilitating the functioning of the theaters; and on the other hand, the world inside the theaters, encompassing the personalities and careers of individual performers, audiences, repertoire, and the adaptation of Chinese performance practices to the American immigrant context. The study also documents the important influence of the theaters on the Chinatown community's sense of its cultural self. Presenting Chinese American music as American music, Rao's work significantly revises understandings of American music by placing the musical activities of an important immigrant group firmly within the bounds of music identified as "American," liberating it from the ghetto of exoticism. Firmly grounded in both Chinese and English language sources, this study offers critical insight into both historical and contemporary questions of cultural identity in the American context.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
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.
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".