Bibliographic record
Abstract
In the period that Don Rubin characterizes by the eventual necessity of “Government Interventions” – that is, 1945 to 1967 – the Anglo-Canadian stage is repeatedly defined as something unformed, primitive and justifiably neglected (131). George Broderson, in a fevered succession of metaphors, calls it a “national impotence,” the “Cinderella of the arts,” and an “undernourished, puling infant” (147); to Nathan Cohen, it is a thing that has “never counted in the life of English-language Canada, [n]or is it likely to in the reasonably foreseeable future” (228). Even to those more inclined to see the glass as half-full, there is no denying the apparent barrenness of Anglo-Canada’s theatre culture; Mavor Moore, for instance, describes it in the mid-fifties as a “tabula rasa,” “propitious[ly]” awaiting inscriptions of “considerable consequence,” but currently blank nonetheless (238). It is thus the paradox of Rubin’s post-war readings in Canadian Theatre History (of which the foregoing are all examples), that they are largely dedicated to bemoaning the lack of a Canadian theatre to historicize. Reading these selections, one gets the impression of a posse of academics impatient for a discipline in which to profess expertise. Conventional wisdom would call this placing the cart before the horse.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.048 | 0.038 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 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".