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Record W1557839251

Critical Discourse Analysis of News Reports on China’s Bullet-Train Crash

2015· article· en· W1557839251 on OpenAlexvenueno aff
Weiwei Wang, Weihua Liu

Bibliographic record

VenueStudies in literature and language · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCritical discourse analysisDiscourse analysisIdeologyConstruct (python library)SociologyContext (archaeology)DialecticChinaCrowd psychologyLinguisticsObject (grammar)Media studiesEpistemologyPoliticsPsychologyPolitical scienceSocial psychologyHistoryComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

The purpose of critical discourse analysis is to study the relationship between language and the ideology embedded in the text of the dialectical aspect. Critical discourse analysis is an emerging method of discourse analysis, which assimilates the results of multi-disciplinary scientific research in linguistics, psychology, sociology, media studies and so on. It attaches importance to all the non- literary discourses, but it takes news discourses as its main research object. Based on Halliday’s three metafunctions, critical discourse analysis in this thesis is done on the basis of news reports about “China’s bullet-train crash” collected from Western media. Fairclough’s three-dimensional model is adopted in the analysis, including description, interpretation and explanation. The aims of the thesis are to reveal how the Western media construct China’s image by using the different linguistic tools, explore the relationship between this constructing mode and big social cultural context, and thus unhidden the ideology embedded behind the social news reports.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.289
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.359
Teacher spread0.328 · 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.

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

Citations4
Published2015
Admission routes1
Has abstractyes

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