COOPERATION OF RESEARCHERS OF KREMENETS TARAS SHEVCHENKO REGIONAL ACADEMY OF HUMANITIES AND PEDAGOGY AND THE NATIONAL UNIVERSITY OF OSTROH ACADEMY IN THE FIELD OF UKRAINIAN SAMCHUK STUDIES
Bibliographic record
Abstract
For the past twenty years, researchers from Kremenets Taras Shevchenko Regional Academy of Humanities and Pedagogy and the National University of Ostroh Academy have been cooperating in the field of Ukrainian Samchuk studies. The article chronologically traces their participation in symposia dedicated, among other things, to the prominent Ukrainian emigrant writer Ulas Samchuk. The author emphasises the special role of Valerii Polkovskyi, Head of the Centre for Canadian Studies of the National University of Ostroh Academy, whose professional interests were aligned with the scholars of our Academy. The author also analyzes the chronicle of the participation of O. Vasylyshyn, I. Kominyarska, O. Pasichnyk and others in the traditional Canadian Scientific Readings. Additionally, the article focuses on the role of Professor P. Kraliuk in the study and promotion of Samchuk's heritage, including the publication of his literary portrait of the Volyn writer by the Kharkiv publishing house Folio. It is noted that with the assistance of P. Kraliuk, almost all of the writer's works were published there.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".