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KYIV LINGUISTIC SLAVISTICS OF THE FIRST QUARTER OF THE XXI st CENTURY: GENERAL OVERVIEW

2024· article· en· W4401402150 on OpenAlexaboutno aff
Liudmyla DANYLENKO

Bibliographic record

VenueMovoznavstvo · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsSlavic languagesLinguisticsQuarter (Canadian coin)DialectologyUkrainianEtymologyTerminologyHistorySlavic studiesFrenchHistorical linguisticsOnomasticsSociologyPhilosophy

Abstract

fetched live from OpenAlex

Ahead of the 17th International Congress of Slavists in Paris in 2025, this article offers a general overview of the directions of scientific research in the first quarter of the 21st century by linguists-slavists of Kyiv, where leading academic and university Slavic centers are concentrated. From the perspective of terminology, linguistic Slavistics includes studies of the languages of Western and Southern Slavs, both separately and in a comparative plan, as well as against the broad background of Slavic linguistics. A brief overview of key works, mainly monographic, lexicographic, and linguistic didactic, is proposed. It is noted that linguists-slavists continue to research Slavic languages in comparative-historical, taxonomic, and communicative-functional paradigms, developing the ideas of leading Ukrainian Slavists of the 20th century and the first quarter of the 21st century — O. S. Melnychuk, V. M. Rusanivskyi, V. G. Sklyarenko, G. P. Pivtorak, O. B. Tkachenko, T. B. Lukinova, A. P. Nepokupny and others. The works of scholars are dedicated to theoretical and practical problems of semantics, etymology, dialectology, onomastics, ethnolinguistics, etc. Among the latest directions within which current issues of Western and Southern Slavic languages are researched are studies in linguocognitology, linguistic pragmatics, and linguofuturology. Attention is drawn to the prospects of Ukrainian linguistic Slavistics, which at the present stage is the work of enthusiasts devoted to their domain. The problem, among other things, is related to the training of personnel in universities, where study hours in the main linguistic and literary disciplines are reduced, interest in postgraduate studies diminishes, and economic difficulties have a negative impact.

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)0.001
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: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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
Published2024
Admission routes1
Has abstractyes

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