Bibliographic record
Abstract
In 1993, I sat down to translate The Dining Room by A.R. Gurney into French. Having seen several high-profile productions in Canada, England and the United States, I was surprised to discover that no French language translation of this play existed. I gave myself the mandate to make available to francophone audiences what I felt was an essential piece of Gurney’s oeuvre and a significant play – if only for its popularity within the contemporary American repertoire. Despite my respect for the play, its author, its structure, its content, its themes, despite my intentions to recreate the specificity of the original version, it still amazes me how quickly I began to adapt the piece rather than to translate it. When confronted with expressions and terms without equivalents in my target language, with cultural references that I knew would be difficult for francophone audiences to understand, with the irreconcilable philological differences that divide any two systems of communication (including the lack of elasticity of the arguably more regulated French language), I rewrote, I cut, I censored, I changed characters’ names. In short, I appropriated the piece in the name of supposed accessibility for an audience and a market I knew well. A year later, when I attended the public reading of my supposed translation at the Théâtre du Nouvel-Ontario in Sudbury, it was clear that I had created an original work, albeit inspired by Gurney’s text. It left the distinct impression that the play had been written for a contemporary French Canadian audience. Gurney had given way to Beddows and the culture and language he represented.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.022 | 0.006 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".