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Record W3089006876

The Tao Te Ching: Translation Theory and Semantic Variance

2020· article· en· W3089006876 on OpenAlexaff
A.M.A. Moore

Bibliographic record

VenueCrossings · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsSource textPoetryBuddhismLinguisticsMeaning (existential)RhymeAmbiguityPhilosophyFrame (networking)LiteratureEpistemologyArtComputer scienceTheology
DOInot available

Abstract

fetched live from OpenAlex

Lao Tzu's Tao Te Ching is a classic and fundamental Ancient Chinese philosophical, poetic, and religious text that dates back to 4th to 6th century BCE. This text is intrinsic to philosophical and religious thought in Taoism, Buddhism, and Confucianism, and is used as a source of inspiration for artists around the world. Because of its inherent poetic ambiguity, some of its translations have been criticized for appropriating Chinese culture for Western perspectives, while others have seen it as a way of making the spiritual text accessible to larger audiences. In this paper, I compare and examine four different English translations of the Tao Te Ching using linguistic frame semantic theory. I argue that semantic variance occurs in each because semiotics are frame dependent, and meaning changes depending on the cultural and temporal frames both the translators bring through their use of fidelity and license when translating, and that the audiences bring when interpreting the artefact. Although variances are present between source text and different translated texts, the translation of the Tao Te Ching has managed to continue to extend its life and bridge the language gaps between cultures, spreading interpretations of its philosophical teachings, and enriching not only the target language, but also the source text in the process.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0010.000
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 head0.054
GPT teacher head0.272
Teacher spread0.218 · 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.

Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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