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Record W2996897732 · doi:10.5539/ijel.v10n1p352

News Framing of the Arab Spring Conflict from the Lens of Newspaper Editorials

2020· article· en· W2996897732 on OpenAlexvenueno aff
Naeem Afzal, Minah Harun

Bibliographic record

VenueInternational Journal of English Linguistics · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
FundersPrince Sattam bin Abdulaziz University
KeywordsNewspaperFraming (construction)MainstreamElitePolitical scienceMedia studiesIdeologyNews valuesNews mediaSociologyPoliticsLawHistory

Abstract

fetched live from OpenAlex

News framing of events often restricts us to either ‘oppose’ or ‘favour’ a particular side/party involved in a conflict. This paper examines the print media framing of the Arab Spring in the editorials of The News International (NI) of Pakistan and Arab News (AN) of Saudi Arabia. The coverage sample consists of newspaper editorials published from January 2011 to December 2012 when the uprising received phenomenal attention from the media worldwide. Qualitative content analysis of 48 newspaper editorials (24 NI/24 AN), demonstrates how senior media workers constructed the Arab Spring as an international conflict. Specifically, the lexical choices of editorial writers reveal that mainstream newspapers in both the countries positively framed the pro-Arab Spring protesters (public), who reportedly desired to bring the ‘change’. On the contrary, the media framing of the uprising also reflects that the newspapers negatively framed the anti-Arab Spring authorities (ruling elite), who reportedly resisted the ‘change’. A future research is recommended to investigate readers’ perspectives, as well, on the media portrayals of the Arab Spring or other similar conflicts which can give insights into how language use can impact and is impacted by ideology, cultural nuances and identity of diverse individuals.

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)0.134
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 score0.877
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.134
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 science0.0010.000
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 head0.048
GPT teacher head0.320
Teacher spread0.272 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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