Bibliographic record
Abstract
espanolEn el presente trabajo, basado en el concepto de “intertextualidad cultural” (Pascua, Adaptacion), me concentrare en la traduccion de algunas referencias culturales que son signos de identidad de una cultura concreta. Tras una breve exposicion de las tendencias traductologicas mas importantes del campo de la literatura infantil durante las ultimas decadas, se mostraran ejemplos de diversos cuentos. En primer lugar, de historias fuertemente arraigadas en la cultura britanica, como es el caso de Alice in Wonderland; luego tomamos ejemplos de otros cuentos de la realidad multicultural que es la literatura infantil canadiense, donde ese aspecto multicultural es lo que refleja la identidad canadiense. Finalmente, presentaremos un nuevo proyecto social: traducir literatura infantil multicultural para una nueva sociedad plural e intercultura EnglishIn the present work based on the concept of “cultural intertextualty” (Pascua, Adaptacion), I will concentrate on the translation of some cultural markers which are signs of identity of a particular culture. After a brief summary on the different tendencies on translating for children during the last decades, I will show some examples from different stories. On the one hand, from tales deeply rooted in the British culture such as Alice in Wonderland, and on the other hand from other tales from part of the multicultural landscape of Canadian children’s literature, where the multicultural aspect is particularly what gives the Canadian identity. Finally, I will present a new social project: translating multicultural children’s literature for a new multicultural society.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".