Telling an Old Story in a New Way: One Reed Theatre Ensemble Devises an Alternative Perspective on a Conflicted History
Bibliographic record
Abstract
In the autumn of 2006 I was fortunate to be in the audience at Studio Léonard Beaulne at the University of Ottawa for a performance of Nor the Cavaliers Who Come With Us by One Reed Theatre Ensemble, winner of the Spotlight Award for outstanding achievement at Toronto’s Summer Works Festival earlier that year. I returned a second time, and then in the spring of 2007 attended a third performance, this time at the University of Toronto’s Glen Morris Studio Theatre. With each viewing I was struck by how notions of history inflect the piece, at the level of both form and contents: In other words, what gets told, by whom and how. What interested me most was how the piece offers an alternative perspective of a particular historical narrative while self-consciously experimenting with modes of performance. Under the direction of Daniel Mroz, assistant professor of Theatre at the University of Ottawa, this work is exemplary of the power of devised theatre to expand the theatrical experience for both actor and audience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".