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Record W4328130069 · doi:10.21226/ewjus639

Media Systems in Unrecognized States: “People’s Media” in “People’s Republics”

2023· article· en· W4328130069 on OpenAlexvenueno aff
Eugenia Kuznetsova

Bibliographic record

VenueEast/West Journal of Ukrainian Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEastern European Communism and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsAuthoritarianismLoyaltySubordination (linguistics)Political scienceIsolation (microbiology)State (computer science)PoliticsDemocracyLaw

Abstract

fetched live from OpenAlex

This paper examines the media systems in the “Donetsk People’s Republic” and the “Luhansk People’s Republic,” both unrecognized states. After a conflict outbreak in 2014, the media landscape in the unrecognized republics acquired the features of an authoritarian media system. Employing qualitative methods (primary source analysis and in-depth interviews), the research explores a combination of instruments that pushed media into an authoritarian mode that entailed declarations of loyalty, severe vertical subordination, predominantly state ownership, and the designation of a military subdivision at the information frontline. Other decisive factors that allowed an authoritarian media system to be instated are the loyalty of the pre-existing media landscape to local authorities and oligarch media owners, the political isolation of the unrecognized republics, and the strong influence of the Russian information space.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.343
Teacher spread0.255 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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