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THE PROBLEMS OF MAZEPIST EMIGRATION IN RESEARCH HERITAGE OF OREST SUBTELNY

2020· article· en· W3148431128 on OpenAlexaboutno aff
Heorhii Potulnytskyi

Bibliographic record

VenueNaukovì zapiski Nacìonalʹnogo unìversitetu Ostrozʹka akademìâ Serìâ Ìstoričnì nauki · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsEmigrationPhenomenonPeriod (music)PoliticsObject (grammar)CreativitySociologyUkrainianPolitical scienceHistoryEpistemologyLawSocial scienceAestheticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

In the article the first attempt is made to evaluate Orest Subtelny’s contribution to the research of the so called Mazepist emigration. For this purpose, the author considers the contribution from two main perspectives: thematic and conceptual. Orest Subtelny’s research work, which is analyzed in the paper, selectively covers four topics from the history of the first period of Ukrainian emigration: the problem of the political aim of Mazepist emigration, the core problems of the international relations between Orlyk and different countries, the problem of the investigation of Orlyk’s Diariush as the source for the general diplomatic history of that period, and the attempt to encompass political emigres of several East European countries and as an entity phenomenon. Through the use of the archival and library sources, the author finds that at different stages of life in the time span of 1970–1990s the problems of Mazepist emigration played a critical role in research of the famous Canadian historian, being the object of his professional interest. Explaining the evolution of Subtelny’s vision of significant problems of the Mazepist emigration, the author concludes that the historian succeeded in possessing the decisive role in the solution of the number of the main research problems of this phenomenon, and was successful in the pioneering formulation of its vision and in proposing an individual attempt to provide an academic solution. This evolution is reflected in a series of monographs, articles, and speeches, written by a scholar mainly in the most mature periods of scholarly creativity – in the time span of 1970–1990s.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.321
Teacher spread0.231 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNaukovì zapiski Nacìonalʹnogo unìversitetu Ostrozʹka akademìâ Serìâ Ìstoričnì naukiSame topicCanadian Identity and HistoryFrench-language works237,207