In Search of ‘Good’ Theatre: Historical Ideals of Quality in Contemporary Times
Bibliographic record
Abstract
The success of a play or work of theatre is based largely upon the reactions of audiences. Audiences collectively decide whether a play is ‘good’ or ‘bad’ and this dictates what shows are produced and who with. If audiences hold the power to say what experiences and who is tolerable on stage, then they also have the ability to dictate who is intolerable. This ability is capable of creating an exclusive environment where some stories are not told, and some people are less welcome than others on the stage. These ideals of ‘good’ are based on long standing value systems derived from theatre history and theorists. Plato, Émile Zola, andDenis Diderot all held strong ideals of what was authentic and therefore tolerable on stage. Plato believed the act of representation to be the key to authenticity, Zola was concerned with the authenticity of voice itself, and Diderot with the stories being told. In considering all three aspects of authenticity this presentation will consider contemporary Canadian theatre examples in comparison to select Shakespearean examples that uphold and subvert the historical conventions. Ultimately, the examples ask how these long-standing values fit in a multicultural Canada, and further within the age of immense globalization.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.062 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".