"Les traductions" du texte théâtral. Bashir Lazhar entre auteure, traducteurs et professionnels de la mise en scène
Bibliographic record
Abstract
– In this article, we will describe the series of textual manipulations that allowed to move from a theatrical text in French, written by a Quebec writer, to its Italian stage reading during a festival held in Rome in October 2011. This passage implied many different manipulation: an interlingual translation (Jakobson) from French to Italian was followed by its intralingual revision by the actor and director; lastly, via an intersemiotic translation, the latter written version was read-staged before an audience. Despite the presence of various semiotic systems, despite the passage of the text from an interpreter to another, the act is – in many ways – the same: an act of translation, based on the same mental operations. Each professional (translators, directors, actors) translates; each translation has its specificity. Résumé – Dans cet article, nous allons suivre la série de manipulations textuelles qui a permis de passer d’un texte théâtral en français, écrit par une écrivaine québécoise, à sa lecture scénique en italien dans le cadre d’un festival de théâtre qui a eu lieu à Rome, au mois d’octobre de 2011. Ces passages ont été multiples : traduction interlinguistique (Jakobson) du français à l’italien ; révision intralinguistique du texte de la part de l’acteur et de la metteuse en scène ; traduction intersémiotique de la version écrite à la lecture-mise en scène face à un public. Malgré la présence de systèmes sémiotiques variés et diversifiés, malgré le passage de la pièce d’un interprète à l’autre, l’acte est un : un acte au sens large traductif, qui s’appuie sur les mêmes opérations mentales. À chaque professionnel (traducteurs, metteurs en scène, acteurs), donc, sa traduction ; à chaque traduction sa spécificité.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".