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Record W1990127317 · doi:10.1080/1057610x.2011.531458

Russia's Counterterrorism Operation in Chechnya: Institutional Competition and Issue Frames

2010· article· en· W1990127317 on OpenAlexaff
Aurélie Campana, Kathia Légaré

Bibliographic record

VenueStudies in Conflict and Terrorism · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAutocracyFraming (construction)Presidential systemAdministration (probate law)Political scienceCompetition (biology)Political economyInterpretation (philosophy)Foreign policyFrame (networking)Public administrationLaw and economicsLawSociologyEngineeringDemocracyPoliticsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

This article analyzes how Russian Federal policies evolved between 1999 and 2005 to justify the policy of “Chechenization” and the legitimization of an autocratic-style regime in Chechnya. It argues that this strategy was progressively elaborated during the conflict as a result of institutional competition between three main Federal agencies (the Presidential Administration, the secret services (FSB)), and the military over the framing of the conflict. This process paved the way for the formation of the “totalizing frame” under the leadership of the Kremlin, which incorporated various discursive constructions into one coherent and exclusive interpretation 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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.382
Teacher spread0.341 · 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 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

Citations13
Published2010
Admission routes1
Has abstractyes

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Same venueStudies in Conflict and TerrorismSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207