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Record W1495232332

Exposure to Political News Accompanying Violent Demonstrations as Reflected in Adopting Conspiracy View against Egypt

2014· article· en· W1495232332 on OpenAlexvenueno aff
Mohamed A. Fadl Elhadidi

Bibliographic record

VenueCross-cultural communication · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperJournalismInterimPublic opinionPoliticsAffect (linguistics)FeelingPower (physics)Political scienceSocial psychologyLawPublic relationsPsychology
DOInot available

Abstract

fetched live from OpenAlex

A field study was conducted at time of violent events that accompanied demonstrations against the Military Council who assumed the power to govern Egypt after 25th January Revolution to determine the effects of exposure to political news on three dependent variables; public opinion belief in conspiracy theory against Egypt, tolerance and affect towards the two parties of the violence (rebels and the Military Council) through the interim transition of military rule. The study found that Egyptian journalism, other political factors and demographic variables predicted the public's adoption of foreign and domestic conspiracy view whether positively or inversely. Unlike newspapers and online journalism, TV satellite channels were the only source predicting public's tolerance and affect. The study also found correlations between respondents' adoption of conspiracy theory and their tolerance judgments and feelings toward the parties of the conflict.

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)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.420
Teacher spread0.363 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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