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Record W2996184208 · doi:10.5539/ijel.v10n1p91

Hedging in Newspaper Editorials in the English and Azerbaijan Languages

2019· article· en· W2996184208 on OpenAlexvenueno aff
Leyla Musa Khanbutayeva

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperPolitenessLinguisticsModalModal verbPoliticsSociologyPolitical scienceMedia studiesLawPhilosophy

Abstract

fetched live from OpenAlex

The present study has been conducted for the linguistic analysis of hedging, which is meant to be an important linguistic feature expressing tentativeness and possibility. The purpose of the study is to investigate hedging devices in English and Azerbaijan economic and political newspaper editorials and to show the frequently used hedges in these stated languages. Basing on the revealed results, it becomes clear that in English newspaper editorials hedging is observed to be more frequently used. It is necessary to underline that the English political and economic newspaper editorials are seen to be more hedged than the Azerbaijan. The article has been focused on the lexical and pragmatic hedges. Hedges pragmatically are realized to be the markers of politeness in the newspaper editorials in the very languages. The modal verbs are considered to be the lexical hedges, and they have been dealt with from this side in the article as well. It is known that modal verbs are used to express the speaker’s attitude to the reality, and they help the speaker to express ideas indirectly as well. The article highlights the necessity of using the modal verbs in the newspaper editorials.

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)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.814
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.029
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 head0.012
GPT teacher head0.283
Teacher spread0.271 · 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 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
Published2019
Admission routes1
Has abstractyes

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