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Record W4385215833 · doi:10.17721/2521-1706.2022.14.3

Taras Shevchenko Kyiv State University’s international cooperation with scientific and educational institutions of Northern and Southern America countries in 1944–1975’s

2022· article· en· W4385215833 on OpenAlexaboutno aff
Oleh Kupchyk

Bibliographic record

VenueAmerican History & Politics Scientific edition · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Science and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)World War IIPolitical scienceLatin AmericansPeriod (music)Economic historyHistoryLaw

Abstract

fetched live from OpenAlex

The world’s leading countries use international cooperation in the education and science field to influence and confirm their authority. The countries of North and South America and the USSR used scientific and educational relations as a means of communication. For Kyiv State University named after T. G. Shevchenko, this provided an opportunity to expand the geography of international relations. Therefore, the aim of the article is a comprehensive study of the connections of KSU named after T. G. Shevchenko with scientific and educational institutions of the countries of North and South America in 1944–1975’s. The scientific novelty of the article lies in the fact that the scientific and educational ties of KSU named T. G. Shevchenko with scientific and educational institutions of the USA and Canada, as well as Latin American countries in 1944–1975’s, have been highlighted for the first time. The methodological basis of the research was the methods of historical retrospection and problem-chronological and analytical methods. The conclusions. It is noted that at the end of the Second World War (1944–1945), the establishment of ties by Kyiv University with educational and scientific institutions of the countries of North and South America was not possible due to the reconstruction of the city and the university itself. And during the period of post-war reconstruction (1946–1950), the Soviet-American confrontation was added to the mentioned problems, which then turned into the Cold War. It is indicated that some scientists from the countries of North America began to visit Kyiv State University named after Taras Shevchenko since the mid-1950s. The prerequisite for this was the liberal socio-political changes in the USSR associated with de-Stalinization (1953–1956) and the Khrushchev Thaw that began in 1956. It is noted that ties between American, Canadian and Soviet universities began to be established after Soviet leader M. Khrushchev visited the USA in 1959. Delegations from American universities visited Kyiv University to familiarize themselves with the organization of educational and scientific work. At the same time, guests from South American countries began to visit Kyiv University. It is indicated that with the establishment of diplomatic relations between the USSR and the Republic of Cuba in 1960, frequent guests at Kyiv State University named after Taras Shevchenko joined Cuban scientists and delegations. Furthermore, Kyiv University has established close cooperation with the Central University of Las Villas Province. From the same year, young people from Latin American countries began to enroll in the Preparatory Faculty for Foreign Citizens. It was clarified that in the mid-1960s Kyiv State University named after Taras Shevchenko’s most active international book exchange was with the Library of Congress in Washington. It was determined that despite the «international détente» in relations between the USA and the USSR in 1969, the ties of American universities with Kyiv State University named Taras Shevchenko in the first half of the 1970s did not go beyond isolated contacts.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
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
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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