MétaCan
Menu
Back to cohort
Record W2157356397 · doi:10.7202/044781ar

A Genealogy of Literal Translation in Modern Japan

2010· article· en· W2157356397 on OpenAlexvenueno aff
Mizuno Akira

Bibliographic record

VenueTTR traduction terminologie rédaction · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLiteral translationLiteral (mathematical logic)Meiji periodLinguisticsCohesion (chemistry)Period (music)LiteratureHistoryCoherence (philosophical gambling strategy)Translation (biology)PhilosophyArtSource textMathematicsAestheticsChemistry

Abstract

fetched live from OpenAlex

In modern Japan, especially in the Meiji period (1868-1912), translations occupied a dominant position in the literary polysystem. This paper claims that, since the Meiji period, “competing translational norms” have existed in the Japanese literary polysystem, which is to say that “literal” (adequate) and “free” (acceptable) translations have existed in parallel, vying for superior status. Moreover, this paper traces the literalist tradition in modern Japan. Though “literal” translation has been widely criticized, the styles and expressions it created have made a significant contribution to the founding and development of the modern Japanese language and its literature. Among the arguments in favor of literal translation, Iwano Homei’s literal translation strategy—the so-called “straight translation”—had different features than the others, and thus the potential to produce translations that maintain the cohesion, coherence, information structure and illocutionary effects of the source text.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.007
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.105
GPT teacher head0.304
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueTTR traduction terminologie rédactionSame topicTranslation Studies and PracticesFrench-language works237,207