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Record W2894797368 · doi:10.3968/10369

Stance in News Discourse: Analysis of Two News Reports in Daily Newspapers in China and the US

2018· article· en· W2894797368 on OpenAlexvenueno aff
Xiaowan Yang

Bibliographic record

VenueCanadian social science · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperChinaNegotiationTransitive relationPolitical scienceTrade warNews mediaPoliticsAdvertisingNews valuesPublic relationsPolitical economyMedia studiesSociologyBusinessLaw

Abstract

fetched live from OpenAlex

The recent Sino-US trade disputes add to the long list of economic and political conflicts between the two largest economies in the world. However, although a trade war is now put on hold with the two countries continuing their negotiations, a different war is fought by major news and business press in both countries to justify the actions taken by each side and gain support from the international community. It therefore becomes a topic of interest as to how the news media make deliberate language choices to influence their readers with their stances and attitudes. This study compares two news reports in daily newspapers in China and the US on a significant trade dispute between China and the US: US imposing safeguard duties on tires from China in 2009. Through Transitivity and Modality analysis, this study aims to demonstrate how news media from rival countries make language choices to help reconstruct events and how different stances and attitudes are implied so as to manipulate the readers to interpret information in an intended way.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.006
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 head0.012
GPT teacher head0.286
Teacher spread0.274 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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