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Record W2541328446 · doi:10.5539/jpl.v9n9p92

The Future of Crises in South Caucasus in the Wake of Russia-West Conflicts

2016· article· en· W2541328446 on OpenAlexvenueno aff
Mohammad Dejkam, Yaghoub-Ali Olad, M. Fatemi

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSecurity, Politics, and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsIslamEthnic groupTerrorismPolitical scienceGovernment (linguistics)Position (finance)Territorial integrityDiversity (politics)Russian federationDevelopment economicsGeographyEconomyPolitical economyPoliticsLawSociologySovereignty

Abstract

fetched live from OpenAlex

South Caucasus region due to various reasons including ethnic diversity, religions and geographical position has long been witnessing various crises such as Karabakh and south Ossetia crisis. Among these, Karabakh crisis has a direct impact on the national interests of Islamic republic of Iran; because, this crisis has been developed in the northern borders of Iran and between the two countries of Azerbaijan and Armenia that in addition to neighboring Iran, both share some historical, cultural, ethnic, and even religious commonalities with Iranian people. In this study, the main question is that in case of failure of the West in confrontation with Russia in Ukraine, Syria, and Iraq, will the West, to compensate its failure, use these crises of the South Caucasus region to inflict the security and interests of Russia? Almost certainly, if the victories of Russian-oriented groups in different areas of the Ukraine crisis as well as the occurrence of significant victories for the government and the people of Syria and Iraq in fighting terrorism such as ISIS and Al-Nusra groups particularly success in reclaiming the occupied cities from terrorists, the West will surely take actions against interests and security of Russia. The triggering one of the dormant crises of south Caucasus by the west is more likely than other crises exist within the borders of the Russian federation and central Asia.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0020.002
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 head0.033
GPT teacher head0.310
Teacher spread0.276 · 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 designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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