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Record W2170777389 · doi:10.7202/017830ar

Translation and Historiography: How an Interpreter Shaped Historical Records in Latter Han China1

2008· article· en· W2170777389 on OpenAlexvenueno aff
Rachel Lung

Bibliographic record

VenueTTR traduction terminologie rédaction · 2008
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsEmperorFrontierChinaInterpreterPoetryPoliticsHistoryLiteratureHistoriographyArtAncient historyLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This article analyzes evidence of interpreting activities in first-century China between the Latter Han (25–220 AD) Chinese administration and non-Han Chinese minority tribes along the then Southwestern frontier (modern Yunnan and the west of Sichuan basin). Besides confirming the existence of interpreting events and the subsequent Chinese translation of three tribal sung poems, a tribal tribute to Emperor Ming (r. 58–75) in a Qiang dialect (without a written language, apparently), this piece of evidence is also of interest to historians of interpreting in four aspects, namely, the nature of interpreting activities in China in antiquity; possible political rewards for the amateur interpreter who was a frontier clerk by profession because of possible translation manipulation; textual traces from the Chinese translation of the poems that suggests a possible manipulation in meaning and style; and the (interpreter’s) superior’s part in the manipulation of the translation, which eventually found its way into the standard history of the Latter Han dynasty. Considering the political needs of Latter Han China to promote the Sinicization cause among non-Han tribesmen in the empire, this article argues, based on analyses of the four factors above, that the interpreter, with his rare knowledge of the tribal tongue in the imperial court, might have consciously shaped the translation of the poems to pander to the liking of his superior and the emperor. This article further shows how and why the interpreter, in his official capacity as a frontier clerk, might have capitalized on his competence in a tribal language and manipulated, albeit mildly, the historical records on the Chinese translation of the poems.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.401
Teacher spread0.202 · 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 designObservational
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

Citations7
Published2008
Admission routes1
Has abstractyes

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