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Record W4200590661 · doi:10.5539/ijel.v12n1p86

Thematic Progression in Economic Discourse: A Case Study of the English-Chinese Reports from The Economist

2021· article· en· W4200590661 on OpenAlexvenueno aff
Fan Li, Wenbo Ma

Bibliographic record

VenueInternational Journal of English Linguistics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsThematic analysisContext (archaeology)Thematic mapMeaning (existential)ChinaSociologyThematic structurePsychologyPolitical scienceQualitative researchSocial scienceGeography

Abstract

fetched live from OpenAlex

The patterns of thematic progression, greatly influenced by culture-peculiar thinking patterns and language-particular features, reflect the integration of form and meaning in the flow of information in discourse. The economic discourse has its distinct linguistic characteristics and important communicative purposes. Thus, related research on the thematic progression of economic discourse is important for us to understand the language use in the context of economic and financial activities and also has important implications for language learning and teaching, translation, automated language information processing etc. This study first employs CiteSpace, a document visualization tool, to review the existing related studies on the economic discourse in China, and then analyzes the major patterns of thematic progression in the economic discourse based on the English and Chinese reports from The Economist. Through our discussion, we aim to explore universals and peculiarities of thematic progression in English-Chinese economic discourse and discuss the reasons attributing to major distinctions between the two languages in terms of thematic progression.

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)0.001
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.318
Teacher spread0.301 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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