Translating Marina Carr for a Brazilian audience: The interweaving of memories in theatre and translation
Bibliographic record
Abstract
In this article, I wish to demonstrate how the theatre translator, when tailoring his/her translation to suit a particular theatre audience, resorts to creative strategies so as to establish dialogues between the exporting and importing cultures s/he is dealing with. Based on both my own translation of By the Bog of Cats… (1998), written by contemporary Irish playwright Marina Carr, and fieldwork carried out with a group of acting students in Florianopolis, Brazil (June 2010), this article shows how the Irish play, when translated into Brazilian Portuguese, creates layers of intertextuality with Brazilian–Azorean folklore and Brazilian theatre tradition, most particularly with Nelson Rodrigues’s modern play Vestido de noiva [The Wedding Dress]. The local language of southern Brazil set in the mystically unsettling space of a bog invited the actors, the director, and the audience members to embark on a hybrid voyage to both familiar and foreign places.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".