Verbatim Theatre and Social Research: Turning Towards the Stories of Others
Bibliographic record
Abstract
This paper analyses the convergence of ethnographic research and Verbatim theatre in both the context of an urban secondary school drama classroom and in two professional theatres in the city of Toronto. This four-year international, digital, collaborative ethnography focuses on performance and its relationship to youth engagement. As part of the larger project, this paper analyses data gathered in the school research site that charted youth reactions to a Verbatim theatre workshop and performance of The Middle Place, a powerful Verbatim play about shelter youth, created by the socially committed theatre company, Project: Humanity. Additional digital data included the subsequent videotaped youth-created Verbatim monologues. The research team also followed Project: Humanity into two professional theatres in Toronto (Theatre Passe Muraille and Canadian Stage) where youth and adult audiences, fresh from seeing The Middle Place, were interviewed about the play, cultural representations of youth, and theatre as a form of social intervention. The third data set occurred back in the classroom of our school research site, where the The Middle Place filtered back into student drama work in surprising ways. To analyse these data, we bring performance theory, Brechtian theory, relational art theory and Foucault’s concept of ‘parrhesia’ to address the ethics of representing trauma and the possibility of ‘fearless speech’. In responding theatrically, these youth offered our research valuable glimpses into the subcultures of urban youth and their theatre-making practices.
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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 | 0.022 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.021 | 0.105 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.003 | 0.005 |
| 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".