Bibliographic record
Abstract
Abstract Ukrainian epics (dumy) first came to the attention of scholars in the nineteenth century when collectors sought folklore that supported nationalist goals. Little is known about early dumy or who performed them, although epics about Turko–Tatar captivity and the Kozak warfare of the fourteenth through seventeenth centuries contain details that correspond to what is known of those periods. Thus, these songs were likely composed contemporaneously with the events they describe. When they were collected in the nineteenth century, dumy were performed by blind, guild-affiliated, mendicant minstrels called kobzari and lirnyky, who adapted their texts for their civilian audiences. Nineteenth-century texts remain duma classics. While efforts were made to compose Soviet-themed dumy and, later, epics about contemporary tragedies like the accident at Chornobyl, these have not entered tradition. Today, dumy are sung by educated enthusiasts, not mendicants. Contemporary kobzari and lirnyky perform at staged events and seek to evoke Ukrainian pride.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".