TRANSLATING BACK P.K. PAGE’S WORK: SOME COMMENTS ON THE TRANSLATION OF "BRAZILIAN JOURNAL" INTO PORTUGUESE.
Bibliographic record
Abstract
Brazilian Journal, da escritora e poeta canadense P. K. Page, é uma obra sobre o Brasil do final da década de 1950, que apresenta esse país a leitores canadenses. Neste trabalho, levanto algumas questões sobre a tradução dessa obra canadense para o português. Meu argumento é o de que a tradução de Brazilian Journal para leitores brasileiros, é, de certa forma, uma retradução, uma vez que a autora, ao escrever sobre o Brasil, “traduziu” o país para um público canadense. Discuto também algumas dificuldades de fazer uma tradução “fiel” do “original” canadense para o contexto brasileiro.Abstract: P. K. Page’s Brazilian Journal is based on the author’s diaries written during the years 1957-1959 and depicts Brazil to Canadian readers. In this paper I argue that the translation of this work into Portuguese is an inviting and challenging task for a Brazilian reader, as the text is about the author’s experience of Brazil and an attempt to translate the country for her Canadian audience. Her text reveals a respect and a love for the “original” observed content, which she wants to master and to which she wishes to be loyal. Page treats some questions of culture and language when she proposes to write about Brazil and these may bring some difficulties to the translator who wants to be “loyal to the original”.
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 | 0.012 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.011 | 0.017 |
| 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".