Bibliographic record
Abstract
I first met the remarkable Toyoshi (Yoshi) Yoshihara in Calgary in 2003, as my first play The Red Priest (Eight Ways to Say Goodbye) was debuting at Alberta Theatre Project's playRites Festival. Born and raised in Tokyo, Yoshihara formally studied Russian language and literature at Waseda University while informally getting involved in theatre after hours in a student club. After a successful career in business, Yoshihara returned to his first love, theatre, and has become Japan's foremost translator of Canadian work. He has translated an astonishing list of Canuck playwrights, from Anne Chislett to Daniel McIvor. Even more interestingly, he has translated the plays of many Albertan playwrights, including John Murrell, Sharon Pollock, Frank Moher and, in recent years, myself. Yoshihara received an honorary doctorate (D. Litt.) from McMaster University in recognition of his introducing Canadian theatre to Japan, and last year, the Playwrights Guild of Canada honoured him with a lifetime membership to recognize his contribution to Canadian playwriting. I spoke with Yoshi from the Banff playRites Colony about his work as a translator and his long-standing connections with Alberta.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.010 |
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".