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Record W3142293223 · doi:10.36968/jpdc-v05-i01-14

Coverage of Islam in the Western Press: Exploring Episodic and Thematic Frames

2021· article· en· W3142293223 on OpenAlexaboutno aff
Hina Nawaz, Prof. Dr. Syed Abdul Siraj

Bibliographic record

VenueJournal of Peace Development & Communication · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsIslamNewspaperFraming (construction)OrientalismReligious studiesPoliticsGuardianFundamentalismGender studiesMedia studiesInterfaith dialogueSociologyPolitical scienceHistoryLawPhilosophy

Abstract

fetched live from OpenAlex

This study is primarily a quantitative content analysis that attempts to explore episodic as well as thematic frames related to Islam and Muslims in the Guardian (UK), the Washington Post (USA), the Australian (Australia) and the National Post (Canada). The research aims to find out the extent and nature of the coverage of episodic and thematic frames in the selected newspapers on Islam and Muslims. The study also aims to explore the tone of coverage of the Western political leaders about Islam and Muslims in the selected newspapers. Drawing on framing theory and Said’s Orientalism/Occidentalism, this study found out that overall the coverage had more negative frames used for Islam and Muslims. Most of the stories were on Stereotypes/Prejudices/fundamentalism followed by Racism/Religious frame. Western newspapers have racial and stereotypical predispositions towards Islam and its adherents. Furthermore, Islam was framed more often as threatful and intolerant religion. It was also found out that in all the selected newspapers, coverage of the Western politicians was more harsh and negative than positive towards Islam and Muslims.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.104
GPT teacher head0.328
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2021
Admission routes1
Has abstractyes

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