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Record W4285302478 · doi:10.18254/s207987840019622-3

Post-Soviet Space in Russian-American Relations (First Quarter of the 21st Century)

2022· article· en· W4285302478 on OpenAlexaboutno aff
Alexandr Kosau

Bibliographic record

VenueIstoriya · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsRivalryPolitical scienceOpposition (politics)Russian federationPoliticsForeign policyQuarter (Canadian coin)Economic historySpace (punctuation)Political economyLawSociologyHistoryRegional science

Abstract

fetched live from OpenAlex

This publication examines the policy of Russia and the United States in the post-Soviet space in the first two decades of the 21st century. The materials were information sources on the foreign policy of the two countries, as well as research by Russian and Western authors using general scientific and special historical methods. The purpose of the article is to examine the role and place of the post-Soviet space in Russian-American relations in the 21st century. In the 21st century, the post-Soviet space has become an arena of geopolitical rivalry between Russia and the United States. This happened due to the cardinal divergence of the national interests of Moscow and Washington in the region. The United States decided to reformat the post-Soviet space, finally ousting the Russian Federation with the prospect of changing the political regime in Russia itself. The realization of this fact by the Kremlin has led to the strengthening, to the best of its ability, of Russian opposition to American penetration into the region. Consequently, in the 21st century, the post-Soviet space has become one of the irritants of Russian-American relations.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.005
Scholarly communication0.0070.003
Open science0.0000.003
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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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
Published2022
Admission routes1
Has abstractyes

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