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Record W4321443601 · doi:10.1080/10584609.2023.2172492

What Drives Perceptions of Foreign News Coverage Credibility? A Cross-National Experiment Including Kazakhstan, Russia, and Ukraine

2023· article· en· W4321443601 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolitical Communication · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsBishop's University
FundersNational Research University Higher School of Economics
KeywordsCredibilityConsistency (knowledge bases)NarrativeMainstreamNews mediaPerceptionPolitical scienceSample (material)Social psychologyPsychologyPublic relationsLawLinguisticsComputer science

Abstract

fetched live from OpenAlex

Research on news credibility and susceptibility to fake news has overwhelmingly focused on individual and message-level factors explaining why people view some news items as more credible than others. We argue that the consistency of the message’s content with the dominant mainstream narrative can have a powerful explanatory capacity as well, particularly in the domain of international news. We test this hypothesis experimentally using a sample of 8,559 social media users in three post-Soviet countries. Our analyses suggest that the consistency with the dominant narrative increases the perceived credibility of foreign affairs news independently of their veracity. We also demonstrate the moderating role of international conflict, government support, and news language in some national contexts but not others. Finally, we report how the effects of these factors on credibility vary according to whether the news items are real or fabricated and discuss the societal implications of our findings.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.481

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 studies0.0010.001
Scholarly communication0.0000.001
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 head0.106
GPT teacher head0.441
Teacher spread0.336 · 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