Bibliographic record
Abstract
Abstract This chapter questions how contemporary arrangements of canonic operas might subvert pervasive notions of Werktreue (faithfulness to the original) that exist for even twenty-first century performers. Drawing on ethnographic research completed in 2016 at the Banff Centre, this chapter examines the rehearsals and performances of No One’s Safe, a workshop production created by Canadian director Joel Ivany, which combines a new English libretto with arias and ensembles chosen from Mozart’s Le Nozze di Figaro, Don Giovanni, and Cosi fan Tutte to depict a whodunit following a murder. The chapter argues that this work demonstrates how experimental arrangements might allow performers to decontextualize the performance of Mozart from both the operatic canon and institutionalized hierarchies of performance. Simultaneously, No One’s Safe also reveals the pervasive ways in which the ghost of Mozart—and correspondingly, “his” authority—haunts even performances that seek to move beyond traditional conventions of the operatic stage.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.018 |
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".