<i>Juliette at Zulu Time</i> : Robert Lepage and the aesthetics of ?techno-en-scene?
Bibliographic record
Abstract
AbstractJuliette at Zulu Time looks at how Robert Lepage's theatre communicates through form that is content, exploring the medium until he discovers something that has an echo in the audience. It also explores how changes in the social context politicize reception of the performance. The article analyses the use of multimedia in two of Robert Lepage's productions — Romeo and Juliette in Saskatchewan (1989) and Zulu Time (1999). Although Romeo and Juliette in Saskatchewan was a text-based production and Zulu Time a devised performance, and there is gap of more than ten years between the two productions, they share a similar use of creative vocabulary taken from different media. This paper explores ways in which these productions borrow and incorporate the language of other media-film, robotics and digital art — within their own performance mise-en-scene to create a techno-en-scene.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".