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Record W1753648067

Literary Translation From Perspective of Reception Theory: The Case Study of Three Versions of Na Han

2013· article· en· W1753648067 on OpenAlexvenueno aff
Wangyue Zhou

Bibliographic record

VenueStudies in literature and language · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsIndeterminacy (philosophy)HorizonPerspective (graphical)RhetoricReception theoryLiteratureInterpretation (philosophy)Style (visual arts)LinguisticsLiterary translationLiterary scienceReproductionSpace (punctuation)PhilosophyLiterary criticismSociologyAestheticsEpistemologyArtMathematicsVisual arts
DOInot available

Abstract

fetched live from OpenAlex

This paper will focus on opinions of two major leaders of reception theory, namely, Iser’s “blanks and indeterminacy” and Jauss’s “horizon of expectations” to explain translators’ creative reproduction of literary translation. The blanks and indeterminacy in literary texts are used to reveal the style and enhance the aesthetic effects of a literary text. Reproduction of the blanks and indeterminacy in literary translation can give the target text reader space to exert their imagination and enjoy the aesthetic effects the original text expresses. This paper is going to explore three English versions from layers of rhetoric devices in Lu Xun’s Na Han, proving that the extent of reproducing the blanks and indeterminacy is determined by the horizon of expectations of different translators as well as their adjustment in merging their own horizon of expectations with that of target text readers. The paper draws a conclusion that there is not definitely good or bad translation as the translators and target text readers have different horizon of expectations in understanding literary works. Different versions give different and various blanks and indeterminacy to readers so that the target readers can give different interpretation of literary works which to some extent contribute to the artistic life of literary works.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.047
GPT teacher head0.312
Teacher spread0.265 · 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 designQualitative
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

Citations12
Published2013
Admission routes1
Has abstractyes

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