Bibliographic record
Abstract
As a child growing up in Detroit, I always viewed (English) Canada more as a close, next door neighbour than as a distant, “foreign” country. So when I saw the Théâtre de la Marmaille (now Le Théâtre des Deux Mondes) perform Crying to Laugh at their us debut in my home town in 1984, I felt an immediate closeness. This is what children’s theatre ought to be, I thought, for they had captured the essence of what it means to be a child in an adult culture (see Klein, “Le Théâtre”). The fact that Monique Rioux played Mea (a linguistic play on the word “me”) only added to my feelings of intracultural connectedness, since Rioux is my Québec-born mother’s maiden name. When I visited Montreal for the first time the following year to explore my dormant Québécois roots through theatre, I felt an overwhelming, yet inexplicable, sensation of having arrived “home.” How could this be – moi, the incompetent French-speaking “foreigner” in this “separate and distinct society”?
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".