The First Ones Back: Actor Testimony and the ‘Show Must Go On’ Ethos at the Stratford Festival of Canada in 2021
Bibliographic record
Abstract
This thesis looks at Shakespearean performance at the Stratford Festival of Canada during its 2021 outdoor ‘pandemic’ season. It argues that the dominant pre-pandemic ‘show must go on’ ethos, that puts institutional well-being ahead of actor well-being, persisted during the pandemic season, even as the Festival implemented painstaking anti-racist and anti-oppressive initiatives. Alongside this argument, the thesis interrogates the ethics around the use of actor testimony in scholarship and attempts to ethically expand its focus from pure Shakespearean performance to include actor statements on institutional practices and policy. Extensive interviews with the 2021 casts of A Midsummer Night’s Dream and R+J are, to this end, at the heart of the study. The paper follows Bridget Escolme’s instruction to use actor testimony dialogically and places these interviews in conversation with contemporary Shakespearean performance theory around labour, disability, diversity, pandemic Shakespeare, the nature of the ‘Shakespearean actor’ in Western culture, and, most importantly, with actor testimony from other sources and the auto-ethnography of the author, a Stratford actor himself. Concentrating on testimony around Zoom, masking, and social distancing during the rehearsal process, the thesis reveals the emotional, physical and financial difficulties the actors took on in order for the show to go on at the Stratford Festival during the Covid-19 pandemic.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.044 | 0.022 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".