ІСТОРИКО-КРАЄЗНАВЧІ ПОГЛЯДИ СТЕФАНА КОВАЛІВА У ПРАЦЯХ УКРАЇНСЬКИХ ГУМАНІТАРІЇВ ЧАСУ НЕЗАЛЕЖНОЇ УКРАЇНИ
Bibliographic record
Abstract
Abstract. The article describes the works of the Ukrainian scholars of the period of independent Ukraine, in which the emphasis on the analysis of S. Kovaliv՚s historical and ethnographic views was directly or indirectly addressed. In the course of the study the authors have systematized, analysed and summarized a number of special and non-special researches: monographs, periodicals, scientific-publicist works, articles and reports in the regional press.In the course of the analysis, it was found that S. Kovaliv was the author of a number of regional studies, several special historical, ethnographic and folklore works. Special attention is paid to the fact that the researchers of S. Kovaliv՚s life and activity during the period of Ukraine՚s independence discovered, characterized and published yet unpublished multi-genre works of the Boryslav writer and public-educational figure. They note that in his writings S. Kovaliv demonstrated the peculiarities of a complex cultural-educational and socio-economic situation in the western Ukrainian lands of the last quarter of the nineteenth and early twentieth centuries.A comprehensive analysis of the works of contemporary intellectuals who, in their research, resorted to the study and analysis of S. Kovaliv՚s multi-genre creative heritage will become a new promising direction for further research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".