Bibliographic record
Abstract
The Nutcracker is the most popular ballet in the world, adopted and adapted by hundreds of communities across the United States and Canada every Christmas season. In this entertainingly informative book, Jennifer Fisher offers new insights into the Nutcracker phenomenon, examining it as a dance scholar and critic, a former participant, an observer of popular culture, and an interviewer of those who dance, present, and watch the beloved ballet. Fisher traces The Nutcracker’s history from its St. Petersburg premiere in 1892 through its emigration to North America in the mid-twentieth century to the many productions of recent years. She notes that after it was choreographed by another Russian immigrant to the New World, George Balanchine, the ballet began to thrive and variegate: Hawaiians added hula, Canadians added hockey, Mark Morris set it in the swinging sixties, and Donald Byrd placed it in Harlem. The dance world underestimates The Nutcracker at its peril, Fisher suggests, because the ballet is one of its most powerfully resonant traditions. After starting life as a Russian ballet based on a German tale about a little girl’s imagination, The Nutcracker has become a way for Americans to tell a story about their communal values and themselves.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.156 | 0.042 |
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".