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Record W3132220755 · doi:10.1002/j.cyo2.20150902.0003

Arab Iranians and Their Social Media Use

2015· article· en· W3132220755 on OpenAlexaff
Ahmed Al‐Rawi, Jacob Groshek

Bibliographic record

VenueCyberOrient · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsConcordia UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsMiddle EastGeopoliticsEthnic groupGovernment (linguistics)Political scienceSocial mediaGender studiesGeographyMedia studiesSociologyPoliticsLaw

Abstract

fetched live from OpenAlex

Abstract Arab Iranians have a special status in Iran and the Middle East. Due to their Arab origins, they are sometimes viewed as the “other” for being different from ethnic Persians, while many Arab countries regard them as the “other” as well perceiving them as being Iranians more than Arabs. This study investigates the media landscape and conflict that is linked to the Ahwazi Arabs with special attention given to social media use. The study argues that Iranian Arabs are used as pawns by two of the regional players in the Middle East - Iran and Saudi Arabia. Within such an analogy, Ahwaz is regarded as a chessboard where geopolitics is continuously played with the systematic and well-planned use of media channels. The examination of social media outlets that are related to Arab Iranians shows that they are either pro-Sunni or pro-Shiite. The resultsindicate that there are very few followers and fans from Iran especially for the Arab Iranians’ anti-government channels, while Shiite SNS outlets—particularly those originating from Iran—garner more followers from inside Iran.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.090
GPT teacher head0.309
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations2
Published2015
Admission routes1
Has abstractyes

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