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Record W1988359720 · doi:10.3138/jrpc.25.3.388

Challenging Authority in Cyberspace: Evaluating Al Jazeera Arabic Writers

2013· article· en· W1988359720 on OpenAlexvenueno aff
Mbaye Lo, Andi Frkovich

Bibliographic record

VenueJournal of Religion and Popular Culture · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamIdeologyMedia studiesCyberspacePoliticsArabicPolitical scienceMeaning (existential)Social mediaPolitical communicationSociologyLawThe InternetEpistemologyLinguistics

Abstract

fetched live from OpenAlex

Abstract: The Arab Spring has been widely branded as a social media revolution. Evidence has shown that many Arab citizens consider Al Jazeera one of the most popular and credible Arab news networks, making it important to explore the manner and the extent to which this media network may have impacted the Revolution. One way to do so is by examining the meaning, configuration, and providers of the Al Jazeera network’s news content. This exploration seems to raise important questions: what are the contents of Al Jazeera’s Arabic politico-religious articles? Are political writers revolutionaries in their views? Do they identify with the Arab mainstream or with a political/ideological group, or do they court the interests of Arab states? To what extent are writers affected by their country of origin, their ideological affiliations, or the country in which Al Jazeera is based—Qatar? This article attempts to answer these questions by analyzing the fluidity and the complexities of a sample of articles collected from Al Jazeera’s Arabic political columns between 30 January and 31 August 2011. In doing so, this article contributes to a timely discussion of social media, religion, and authority in the Arab world by presenting a case study of the political content of one of the Arab world’s leading media outlets.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.034
GPT teacher head0.359
Teacher spread0.325 · 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 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

Citations5
Published2013
Admission routes1
Has abstractyes

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