News Framing of the Arab Spring Conflict from the Lens of Newspaper Editorials
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".