Bibliographic record
Abstract
Cécile Marshall, whose doctoral thesis analysed Harrison’s poems, films and plays (Université Michel de Montaigne, Bordeaux 3, Bordeaux, France), went on to translate some of these works into French. In this article, she concentrates on the more creative side of her engagement with Harrison’s poetry, her activity as Harrison’s French translator. Providing a few samples from her French translations, she describes the processes at work in translating rhymed verse into French, acknowledging difficulties, doubts and discoveries, and analyses the specificities of rhythm and meter in Harrison’s poetry that must flow, even if differently, from one language into another. She also traces the different French translations, from Quebec to Belgium and France from the late 1990s onwards which show the appeal of Harrison’s poems, as well as the difficulty of making this prolific poet accessible in translation. Cécile Marshall comments on her own contributions as a translator of Harrison into French for different occasions: poetry readings and screenings in Paris or Nantes; publications in monolingual or bilingual editions. She also underscores the vital help and encouragement she received from Harrison who was always attentive to the music of the French versions of his own poetry, a collaboration that owed the poet and his translator to be honoured with the Strasbourg European Prize for Literature in 2010.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".