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Record W4403170350 · doi:10.33458/uidergisi.1454053

Sergei I. ZHUK, KGB Operations against the USA and Canada in Soviet Ukraine, 1953-1991 (London and New York, Routledge, 2022)

2024· article· en· W4403170350 on OpenAlexaboutno aff
Mustafa Koç

Bibliographic record

VenueUluslararası İlişkiler Dergisi · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic historyPolitical scienceRegional scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Professor Zhuk’s “KGB Operations against the USA and Canada in Soviet Ukraine, 1953- 1991” focuses on the post-Stalin Cold War period, when Soviet Ukraine was gradually opened to American and Canadian visitors and combines counter-intelligence documents in the 1st (and 16th) fund of Security Service of Ukraine (SBU) archive with the Committee for State Security’s (KGB) official correspondence and reports to the political leadership of Soviet Ukraine. The first and most important historical source of the book which follows a chronological and thematic sequence reflecting the story of special KGB operations is the reports of various KGB agents who participated in KGB counterintelligence operations. The second group of “unexpected” sources, as the author calls it, consists of interviews with retired KGB officials in Kyiv and Dnipro. In the first part of the book (pp. 1-94), it is emphasized that the most important target of the KGB in the geopolitical conflict was Ukrainian nationalism, which was linked to and financed by Americans, and from 1953 to 1991, almost 50% of all criminal cases were devoted to this “dangerous” issue of Ukrainian nationalism. The author states that the second target of Ukrainian KGB was Jewish nationalism, while the third target was religious sects and the fourth target was American espionage. The most interesting narrative of the first part is the “Yankees case” involving Valentina Fedorovna Safianova and seven so-called nationalist Jews. Professor Zhuk, who mentioned in his work that the KGB adopted an antiSemitic approach despite the Soviet Union’s (USSR) official distancing from anti-Semitism, states that the KGB used Ukrainians and Russians for the needs of Soviet intelligence. The Ukrainian diaspora in America in the 1960s became the “useful means” of the Soviet KGB and one demonstrative example used by the author, Zhuk, is Peter Krawchuk who visited Soviet Ukraine as a member of Canadian Ukrainian Communist Delegations almost every year starting from 1947. Zhuk wrote regarding Peter Krawchuk that “Their material wellbeing, even their Canadian businesses depended on those relations (p. 66)”.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.285
Teacher spread0.257 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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