“Dobro” and “blaho” in Ukrainian texts of the first quarter of the 17th century: vocabulary translations
Bibliographic record
Abstract
The article is devoted to the history of the formation of theological and philosophical conceptual apparatus in Ukrainian texts of the first quarter of the 17th century. Analysis of the principles of the use of lexemes "dobro" and "blaho" in translations of Greek patristic and ascetic works, showed the following trends: (1) Principles for the use of both lexemes depended on the target language – old Ukrainian or Church Slavonic. (2) In the texts in Church Slavonic: the predominance of lexeme "blaho" is fixed over the lexeme "dobro", that in general rather corresponds to the Greek prototype; "blaho" is consistently reserved for the "high" style and defines the semantic fields associated with the sacral area; the lexeme "dobro" is mainly used at the level of everyday language. (3). In the texts written in old Ukrainian language: the lexeme "blaho" is missing, it is replaced everywhere by the lexeme "dobro"; the use of the lexeme "dobro" is no traceable distinction between the sacral and the profane semantic fields. (4). The line of demarcation in the ways of speaking that fixes the differences between high theological discourse that operates with the concepts and everyday language, is not only on the level of language choice (the sacral Church Slavonic or "simple" old Ukrainian), but also on the level at verbalized intellectual activity, fixed in the specific joint variations of word usage within each linguistic usage.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".