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Record W4413572094 · doi:10.1080/10758216.2025.2538776

Between Loyalty, Chechen Nationalism, and Regime Survival: A Discourse Analysis of Kadyrov’s Telegram Channel during Russia’s Invasion of Ukraine

2025· article· en· W4413572094 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

VenueProblems of Post-Communism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsUniversity of Ottawa
FundersEconomic and Social Research Council
KeywordsChechenNationalismLoyaltyChannel (broadcasting)Political scienceHistoryAncient historyTelecommunicationsEngineeringLaw

Abstract

fetched live from OpenAlex

This article analyzes 2,098 posts from Ramzan Kadyrov’s Telegram channel “Kadyrov_95” between February 24, 2022, and October 16, 2023, to examine how he uses the Russo-Ukrainian war to consolidate power. Using Natural Language Processing, it reveals how Kadyrov’s messaging centers on glorifying his father, Akhmat Kadyrov, to legitimize his rule. The study explores how social media reinforces Kadyrov’s loyalty to Vladimir Putin, amplifies his federal political influence, and secures regime durability. The war serves as a strategic platform for promoting Kadyrov’s family members, reinforcing his cult of personality, and strengthening control over Chechnya.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.032
GPT teacher head0.337
Teacher spread0.305 · 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