Institutional Responses to #MeToo: A Conversation
Bibliographic record
Abstract
Theatre administrators, artistic directors, and heads of programs from across Canada have a conversation about how institutional policies and cultures have shifted in the wake of #MeToo. The conversation features Kristian Clarke, Executive Director of the Dancer Transition Resource Centre (DTRC); Frédéric Dubois, Director of the French Section, National Theatre School; Melanie Dreyer-Lude, Chair of the Department of Drama at the University of Alberta; Weyni Mengesha, Artistic Director of Soulpepper Theatre; Alisa Palmer, Artistic Director of the English Section, National Theatre School; Kathryn Shaw, Artistic Director of Studio 58 at Langara College; and Jacqueline Warwick, Director of the Fountain School of Performing Arts, Dalhousie University. The participants reflect on the challenges of taking stock of the impacts and effects of a cultural movement that is still unfolding and the ways in which #MeToo has changed the relationship between training institutions and the performing arts industry.
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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 | 0.088 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.013 | 0.017 |
| 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".