Bibliographic record
Abstract
This paper is intended to study translation from the viewpoint of “intertextuality”. By quoting Kristeva, Barthes and Hatim’s view of intertextuality, author works out a more applicable procedure for translator to render intertextual reference in poetry by combing Hatim’s approach with Nida’s “dynamic equivalence”. This essay is composed in the hope of rendering a new dimension to translation studies. Key Words: intertextuality, dynamic equivalence, translation of poetry Resume: Ce texte est destine a etudier la traduction du point de vue intertextualite . Tout en citant les idees de Kristeva , Barthes et Hatim , l’auteur arrive a degager une procedure plus applicable pour les traducteurs afin de presenter la reference intertextuelle dans la poesie a travers la combinaison de l’approche de Hatim avec celled de l’equivalence dynamique de Nida . Cet essai est redige dans l’espoir de donner une nouvelle dimension a l’etude de traduction Mots-cles: intertextualite, equivalence dynamique, traduction de la poesie
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".