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Record W2083477432 · doi:10.7202/1024175ar

The Translation of Wordplay from the Perspective of Relevance Theory: Translating Sexual Puns in two Shakespearian Tragedies into Galician and Spanish

2014· article· en· W2083477432 on OpenAlexvenueno aff
Francisco Javier Díaz-Pérez

Bibliographic record

VenueMeta Journal des traducteurs · 2014
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsPunRelevance theorySource textRelevance (law)LinguisticsPerspective (graphical)Equivalence (formal languages)Relation (database)Target textContext (archaeology)Computer sciencePsychologyCognitionPhilosophyHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

The present paper aims to analyse the translation of puns from a relevance-theory perspective. According to such theoretical framework, the relation between a translation and its source text is considered to be based on interpretive resemblance, rather than on equivalence. The translator would try to seek optimal relevance, in such a way that he or she would use different strategies to try to recreate the cognitive effects intended by the source writer with the lowest possible processing effort on the part of the target addressee. The analysis carried out in this study is based on two tragedies by Shakespeare – namely, Hamlet and Othello – and on five Spanish and two Galician versions of those two plays. The strategies used by the translators of those versions to render sexual puns have been analysed, focusing not only on the product but also on the process. The selection of strategy is determined, among other factors, by the specific context and by the principle of relevance. In those cases in which there is a coincidence in the relation between the levels of signifier and signified across source and target language, translators normally opt to translate literally and reproduce a pun based on the same linguistic phenomenon as the source text pun and semantically equivalent to it. In the rest of the cases, the translator will have to assess what is more relevant, either content or the effect produced by the pun.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.308
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2014
Admission routes1
Has abstractyes

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