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Record W2759341078 · doi:10.7202/1041026ar

Translation and Ideology: A Study of Lin Zexu’s Translation Activities

2017· article· en· W2759341078 on OpenAlexvenueno aff

Bibliographic record

VenueMeta Journal des traducteurs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
FundersWuhan UniversityChina Scholarship CouncilMacquarie University
KeywordsIdeologyGovernment (linguistics)State (computer science)NewspaperPolitical scienceTranslation (biology)Divergence (linguistics)LawSociologyMedia studiesLinguisticsPhilosophyPoliticsComputer science

Abstract

fetched live from OpenAlex

This paper describes a brief study of Lin Zexu’s translation activities from the perspective of ideology. Lin was not a translator himself, but an initiator and patron of translations. He organised translation activities with sources from foreign newspapers and books to help his anti-opium campaign and resistance to British invasion. Translations from foreign sources were not welcomed by the Qing government and translators were even regarded as traitors. Lin, however, had a contrasting attitude towards translation. To Lin, translation was a way to learn about the outside world and to learn from it. The Qing government, on the other hand, held the view that translations of foreign documents were of little use. The difference between Lin’s view and that of the Qing court can be seen as an ideological divergence between Lin and the government he served. This culminated in the expulsion of Lin from the government, his exile and the termination of his translation activities. This shows how a state instigated ideological position can predominate over an oppositional ideology – in this case to the detriment of the state.

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)0.007
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0110.009
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.136
GPT teacher head0.347
Teacher spread0.211 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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