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Record W4323314748 · doi:10.1080/15456870.2023.2187801

War propaganda effectiveness: a comparative content-analysis of media coverage of the two first months of Russia’s invasion of Ukraine

2023· article· en· W4323314748 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

VenueAtlantic Journal of Communication · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNewspaperMass mediaPoliticsPolitical scienceContent analysisGovernment (linguistics)Spanish Civil WarMedia studiesAdvertisingEconomic historyLawSociologyHistorySocial scienceBusiness

Abstract

fetched live from OpenAlex

The article discusses the coverage of the two first months of Russia’s invasion of Ukraine by mass media in four countries, Russia, Ukraine, the United States, and the United Kingdom. In total, publications in seven mass media (online news portals and print newspapers) were content analyzed, along with war-related speeches of political leaders in those countries. An original method for assessing war propaganda effectiveness was used. It implies tracking the propagation of a political leader’s message through the mass media. The fewer distortions in the process, the more effective propaganda is. With the help of this method, it was determined that despite the severe restrictions imposed by the government, war propaganda in Russia appeared to be relatively ineffective. President Putin’s messages tended to be ‘lost in transmission.’

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.091
GPT teacher head0.349
Teacher spread0.258 · 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