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Record W3010971921 · doi:10.5539/ijel.v10n3p115

‘Future Talk’ in Newspaper Editorials: Predictions and Their Role in Argumentative Discourse

2020· article· en· W3010971921 on OpenAlexvenueno aff
Farzana Masroor, Muhammad Yousaf, Azhar Habib, Ijaz Ali Khan

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperArgumentativePersuasionArgument (complex analysis)Action (physics)PreferenceArgumentation theoryPsychologyPolitical scienceAdvertisingSociologySocial psychologyPublic relationsLinguisticsMedia studiesBusinessLaw

Abstract

fetched live from OpenAlex

Newspaper editorials are known for taking a stance while fulfilling their goals of persuading the audience. In this regard, making future predictions is a crucial strategy in the argument structure of editorials. They are considered as risky acts since they are meant to outline future course of action as well as outcomes of such actions for their audience. This research is focused on the analysis of the speech acts of predictions among newspaper editorials of Pakistani, American and Malaysian newspapers. The analysis is focused on the exploration of forms, force and occurrence of these acts. The results indicate the preference of Pakistani and American newspapers in using strong predictions. The Malaysian newspaper meanwhile is found to be less explicit when predicting the future. This is indicated by less use of the strategy as well as adoption of implicit ways to express propositions related to the future. The results affirm the role of editorials as opinion leaders in their respective societies and the differences across cultures can be interpreted with respect to the extra linguistic and contextual factors that control editorial structures and strategies. The findings of the study are useful for future researchers to explore the relationship of language and its communicative purpose especially when fulfilling the goals of persuasion across cultures and contexts.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.010
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 head0.014
GPT teacher head0.284
Teacher spread0.270 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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