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Record W2883524799 · doi:10.3968/10213

John Fryer’s Contribution to Standardization of Translated Scientific Terminology in Modern China

2018· article· en· W2883524799 on OpenAlexvenueno aff
Lifang Yang, Changbao Li

Bibliographic record

VenueStudies in literature and language · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies in Science
Canadian institutionsnot available
Fundersnot available
KeywordsTerminologyStandardizationChinaMirroringHistoryScientific terminologyLiteratureLinguisticsSociologyPolitical sciencePhilosophyArtLawArchaeologyPhysics

Abstract

fetched live from OpenAlex

John Fryer was a British missionary in the late Qing Dynasty who came to China and was employed by The Translation Department of Kiangnan Arsenal. He has been engaged in the translation work for over 28 years, not only having translated a great deal of Western scientific works into Chinese, but also having contributed greatly to the standardization of the scientific terminology translation. This paper first attempts to probe into Fryer’s scientific translation practice and his translation ideas, and then points out that Fryer’s major contributions to the standardization of the scientific terminology translation in Modern China are that the magazine Ko-chih-hui-pien he established had helped greatly with the popularization of modern scientific knowledge, that the book Mirroring the Origins of Chemistry he translated had paved the way for the term translation of modern chemical elements, and that various lists of bilingual technical terms he made, to a great degree, had standardized the translation of scientific terminology.

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)0.015
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.995
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0050.012
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.304
Teacher spread0.283 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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