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Cultural and educational work of the Harvard Ukrainian Research Institute for preserving the national identity in the second half of the XX century (on materials of Ukrainian-language periodicals of the US diaspora)

2021· article· en· W4206327032 on OpenAlexaboutno aff
Леся Біловус, Oksana Homotyuk, Nataliia Yablonska

Bibliographic record

VenueBulletin of Luhansk Taras Shevchenko National University · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianExhibitionEntertainmentDiasporaIdentity (music)Media studiesSociologyInstitutionNational identityPolitical scienceSocial scienceGender studiesHistoryLawArt historyLinguisticsArtAesthetics

Abstract

fetched live from OpenAlex

The article shows the activity of one of the leading Ukrainian scientific institutions in the diaspora, in particular the Harvard Ukrainian Research Institute, in the sphere of preserving the national identity. The main source base of the study was Ukrainian-language publications of the Ukrainian diaspora in the United States. The main directions of cultural and educational activity of this institution are described i.e. activity of Harvard Ukrainian Summer Institute, opening of three departments of Ukrainian studies in this prestigious university, scientific researches, publications presenting results of Ukrainian scientists and the ones about Ukraine, increase of library funds of Ukrainian, scientific conferences, book exhibitions, art exhibitions, cultural and entertainment events. The interaction of scientists from the USA and Canada in the field of Ukrainian studies, which resulted in the creation of the Standing Conference of Ukrainian Studies, is presented. The main topics of Harvard Ukrainian Studies in the study period are considered. The focus is on the first publications on the Holodomor, which were made at the Harvard Institute. The activities of the Harvard Ukrainian Research Institute are useful as it brings the light to the Ukrainian problem or segment of a particular topic from the Ukrainians’ point of view.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.063
GPT teacher head0.356
Teacher spread0.292 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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