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Record W2100859808 · doi:10.7202/000576ar

What’s Modern in Chinese Translation Theory? Lu Xun and the Debates on Literalism and Foreignization in the May Fourth Period

2003· article· en· W2100859808 on OpenAlexvenueno aff
Leo Tak-hung Chan

Bibliographic record

VenueTTR traduction terminologie rédaction · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)ChinaLiteratureContext (archaeology)IndigenizationNew Culture MovementRomanceTranslation studiesDissenting opinionPhilosophyHistorySociologyArtAestheticsLawPolitical science

Abstract

fetched live from OpenAlex

This article attempts to assess the contribution of Chinese translators and theorists of the twenties and thirties, in particular the famous writer Lu Xun, whom I consider the first modern translation theorist in China. It is with him that China entered its modern phase in translation. Not only did he advocate retaining the foreignness of the original text, in a way reminiscent of the entire tradition of German Romantic translation theorists from Schleiermacher to von Humboldt to Goethe; he also explored in his own translations the possibilities for enriching the Chinese language through the importation of Europeanized structures and expressions. It is these foreignizing impulses that set Lu Xun apart most clearly from pre-modern Chinese theorists. At the same time, these impulses connect him with leading giants of translation theory like Nabokov and Benjamin (who emphasized the importance of the literal method in translation) on the one hand, and Venuti and Holmes (who highlighted processes of indigenization and exoticization in translation) on the other. Lu Xun’s ideas had a particular place in the wider cultural and historical context. Views similar to his had been advocated by his predecessors at the beginning of the century, whose attempt to Europeanize the classical language did not, unfortunately, find a large following. In his own time, Lu found ardent supporters among friends and colleagues who either (a) suggested thorough Europeanization, or (b) preferred limited Europeanization. Dissenting views, however, were clearly voiced by some of the other leading writers of the day. So there were (a) those who favored the use of a language based on the actual words spoken by the populace and (b) those who queried why one should not learn a foreign language and read the original instead. My article deals at length with the debates among these theorists and seeks to understand them from the perspective of contemporary Western translation theory.

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)0.001
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 score0.574
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.050
GPT teacher head0.307
Teacher spread0.257 · 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

Citations13
Published2003
Admission routes1
Has abstractyes

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