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Record W4285013304 · doi:10.5539/ells.v12n3p7

An Investigation on English Translations of Culture-Loaded Words in The Analects of Confucius from the Eco Perspective: A Case Study of the English Translation of Lectures on China’s Traditional Political Thoughts

2022· article· en· W4285013304 on OpenAlexvenueno aff
Dan Yang

Bibliographic record

VenueEnglish Language and Literature Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyTerminologyPerspective (graphical)ChinaPoliticsLinguisticsChinese cultureSociologyLiteraturePhilosophyComputer scienceArtArtificial intelligencePolitical scienceLaw

Abstract

fetched live from OpenAlex

The Analects of Confucius are classic works of ancient Chinese Confucian school, which contains a lot of culture-loaded words. And James Legge, Gu Hongming and Arthur Walley’s English translation of Analects is widely spread and highly recognized. Therefore, this paper will take Lectures on China’s Traditional Political Thoughts as an example to study the translation of culture-loaded words in three translated versions of The Analects of Confucius from the eco perspective. Relying on the Chinese ideological and cultural terminology Library under the project of “Chinese ideological and cultural terminology communication project”, this paper mainly combs and sums up the culture-loaded words in The Analects of Confucius respectively translated by James Legge, Gu Hongming, Arthur Waley. Based on the perspective of eco translatology, this paper makes a comparative study on translation methods of different schools from the perspectives of language, culture and communication, so as to improve the academic preciseness and accuracy of the translation.

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 score0.041
Threshold uncertainty score0.405

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 studies0.0010.000
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 head0.041
GPT teacher head0.292
Teacher spread0.251 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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