Power Struggle Between Supreme Court and the Government: Ideological Role of Pakistani Print Media in Representation of Swiss Letter Issue
Bibliographic record
Abstract
Newspaper headlines constitute an essential part of media discourse, which is an important field of research in Discourse and Communication Studies. Particularly, certain features of news headlines and their role in observing and directing readers’ attention have made the interface between linguistic analysis of newspaper headlines and the opinion building of the readership. In order to explore the ideological role of print media in representation of Swiss Letter Issue which resulted nullification of an elected prime minister of Pakistan by Supreme Court and the next PM of the same political party was also facing the same challenge. Three widely distributed English newspapers (The News International, DAWN and The Nation) have been selected using purposive sampling technique. Designated time ranges between 1st July 2012 and 31st December 2012, very significant pre-election period in Pakistan. To find the coverage given to the issue by the selected newspapers, total 319 related headlines were found. The data were selected through simple random sampling technique. The obtained data has been analysed by using Faiclough’s three-dimenional model of critical discourse analysis, and simple statistical analysis as well. The findings of the study indicate that print media of Pakistan used manipulative strategies in construction of headlines on Swiss Letter Issue and represented the issue in a biased manner.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".