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Record W1868339436 · doi:10.5539/ells.v5n3p118

Translating Conceptual Metaphors in Chinese Stock News Report: A Web-Based Study

2015· article· en· W1868339436 on OpenAlexvenueno aff
Mei-Ya Liang, Jiafeng Liu

Bibliographic record

VenueEnglish Language and Literature Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersSouthwest University for NationalitiesFundamental Research Funds for the Central UniversitiesSouthwest University
KeywordsConceptual metaphorMetaphorConceptual frameworkConceptual systemComputer scienceMeaning (existential)Conceptual modelLinguisticsPsychologySociologyEpistemologyPhilosophySocial science

Abstract

fetched live from OpenAlex

Previous studies of stock news report mainly focused on the identification of conceptual metaphors in Chinese or English stock news report. Few of them further analyzed the translation strategies of conceptual metaphors between English and Chinese. Basing on the analysis of Chinese stock news report on FORBESCHINA.COM, this paper investigates conceptual metaphors of UP and DOWN, LOCOMOTION and WAR, and discusses their translation strategies: maintaining original conceptual metaphor, substituting original conceptual metaphor, and deleting the original conceptual metaphor with meaning-kept.

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)0.004
metaresearch head score (Gemma)0.015
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0030.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.328
Teacher spread0.303 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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