Bibliographic record
Abstract
This issue of Theatre Research in Canada/Recherches théâtrales au Canada marks the official changing of the editorial guard. For the last seven years, Glen Nichols has shown exemplary leadership as General Editor, overseeing the publication of sophisticated, award-winning, discipline-shifting articles and theme issues on such topics as intermedial performance, intercultural performance, and francophone theatre in western Canada. Needless to say, I have some rather large shoes to fill and so I’d like to take this opportunity to thank Glen for his kindness, patience, and support throughout the transition period. I am also grateful to Stephen Johnson, Barry Freeman, Erin Hurley, Louise Ladouceur, Kelsy Vivash, and Shelley Liebembuk for their encouragement and hard work in the past year.
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 | 0.008 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.017 |
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".