An Historiographical Reading of the Founding of Canada's National Theatre School
Bibliographic record
Abstract
On November 2, 1960, French director and teacher Michel Saint-Denis declared the National Theatre School of Canada (NTS)the nations first professional theatre training institutionopen, and the Canadian theatreits English and French traditionsentered a new stage of professional development. But how did it get there? \nThis historiographical study of the NTS founding is the first thorough examination of the complex process through which the only bi-cultural, co-lingual school in Canada was established, from first inklings in the nineteenth century to its official opening in 1960. This dissertation utilizes Thomas Postlewaits four-part model of historiographical theory to explore and document the various contexts which helped to shape the ways in which the School was structured, operated, and received by the public at the time it opened. \nWhile the National Theatre School of Canada is clearly recognized as an important part of the professional Canadian theatre, it is argued here that the details of the Schools foundingeven nowremain contradictory, forcing the discussion to focus more on the results of the school after it officially opened rather than on the ideas which created it. After half a century, it seems time to articulate, at the very least, those founding debates, adding them to Canadas theatre history and giving them relevance in todays increasingly diverse Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.030 | 0.024 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".