Bibliographic record
Abstract
http://dx.doi.org/10.5007/1980-4237.2014n16p118Como o ensaio de um espetáculo cuja estreia está, ainda, por vir, este exercício acompanha, em estilo experimental, a cena da tradução da escritora e tradutora canadense radicada em Paris Nancy Huston. O objetivo é apresentar a genealogia de uma ética que, ao cortar a lógica da repetição alienadora de determinado atributo (o “outro”, a “letra”, a “diferença”...), eleva o intervalo do desejo, transformando-se ela mesma numa tarefa sempre – ainda − por vir.ABSTRACTResembling the rehearsal of a spectacle whose debut is yet to come, this essay follows, in an experimental style, the translation scene of Paris-based Canadian author and translator Nancy Huston. The aim is to exhibit the foundation of an ethics which, by cutting up the logic of an alienating repetition of a given attribute (the so-called “other”, “letter”, “difference”…), enhances the interval of the desire, becoming itself a task always [yet] to come.Keywords: translation and ethics; selftranslation; becoming.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".