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Record W4405121460 · doi:10.16985/mtad.1537017

In the Russia, Türkiye and Iran Triangle; Karabakh

2024· article· en· W4405121460 on OpenAlexaboutno aff
Vugar Akifoğlu

Bibliographic record

VenueMarmara Türkiyat araştırmaları dergisi · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLiterary, Cultural, Historical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsArmenianPolitical scienceQuarter (Canadian coin)Soviet unionGeographyCentral asiaAncient historyEconomyEconomic historyHistoryLawPoliticsArchaeology

Abstract

fetched live from OpenAlex

Karabakh, located within the triangle of Turkey, Russia, and Iran, is a region of significant strategic importance. It particularly serves as a gateway connecting Turkey to Central Asia. Throughout history, Karabakh has been part of Azerbaijan’s territory. From the first quarter of the 1800s, Armenians, along with people from regional powers such as Russia, Turkey, and Iran, migrated to the region. Especially Russia and European countries, aiming to separate Turkey from Central Asia, supported the migration of Armenians to the region. After the fall of Tsarist Russia, the Soviet Union supported Armenian territorial claims on various platforms within the framework of its own interests. This study examines Armenia’s policies of seizing Azerbaijani lands throughout history and the approaches of neighboring countries to the situation. Specifically, it analyzes the policies of the three regional countries during the First and Second Karabakh Wars, the November 10 ceasefire agreement that ended the war, the crimes committed by Armenians during the war and their withdrawal from Karabakh, and the international response to these issues based on various sources.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.005
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.028
GPT teacher head0.230
Teacher spread0.202 · 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
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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