Creating the space of truth in the make-believe world of the theatre: An interview with Peter Sellars
Bibliographic record
Abstract
Abstract Peter Sellars is one of the most celebrated directors of opera, theatre and festivals in the contemporary West. He is well known for his adaptations of classic works in response to the political, social and economic conditions at the time of staging, while his activist politics and lack of reverence for hierarchical institutions frequently polarizes response to his work. In a spirited interview, conducted by academic and critic Karen Fricker in July 2013 as part of the Leverhulme Olympic Talks on Theatre and Adaptation, Sellars discusses his background in puppet theatre, his early career at Harvard University and the American National Theatre, and several of his important productions including Ajax (an adaptation of Sophocles by Robert Auletta, American National Theatre, 1986); Children of Herakles (Euripides, premiered at the Ruhr Triennale, 2002); and Desdemona, a music theatre piece created with writer Toni Morrison and singer Rokia Traoré in 2012.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.030 | 0.038 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".