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Record W4410160759 · doi:10.31891/2415-7929-2021-21-10

СТИЛЬОВІ ОСОБЛИВОСТІ ЛІРИКИ ОЛЕКСИ ГАЙ-ГОЛОВКА

2021· article· en· W4410160759 on OpenAlexaboutno aff
Л. КАПЛИЧНА

Bibliographic record

VenueCurrent issues of linguistics and translation studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Social Development in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The article is an attempt to comprehend the stylistic specifics of the lyrical works of the Ukrainian writer Oleksa Hai-Holovko (1910–2006), who lived in Canada. His diverse artistic heritage (poetry, prose, memoirs, literary criticism, study of literature) includes dozens of books and articles published mainly in a multicultural environment (Poland, Germany, England, Canada).The author did not recognize the modern style,he even ridiculed the modernists, strictly adhered to the rational concept of modeling the artistic world. It is proved that the structure of individual poems the poet reinforces with a kind of psychologism, which is specified by expressive coloring.The subject during the utterance is commensurate with the object of the artistic image, so its inner world is equivalent to the sphere of experiences, emotions, feelings,it appears to the reader energetically and deeply dynamically.It has been found out that the poet framed the perfection of the idea by trope means, the words of figurative meaning became the decoration of the correlation (ratio) of aesthetic elements of lyricizing“I –the Other”. Hai-Holovko’s poems are full of symbols, semantic nuances that convey the mood of the lyrical narrator, whose narration is projected on the reader, aesthetic perception and rethinking of ontological parameters.Stylistic peculiarities of the poet’s lyrics can be clearly traced on the receptive, aesthetic, versification levels.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.960
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.222
GPT teacher head0.492
Teacher spread0.271 · 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 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
Published2021
Admission routes1
Has abstractyes

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