Bibliographic record
Abstract
Inter-war Berlin was one of the centers of Ukrainian emigration. The institution that united practically all Ukrainian intelligentsia in Berlin in the 1920s and 30s was the Ukrainian Scientific Institute (UNI), founded in 1926 on the initiative of Pavlo Skoropadsky. The main directions of the UNI’s activities (which included four research chairs) were, on the one hand, financial aid for Ukrainian students at German universities, and, on the other hand, the development of Ukrainian studies in Germany. Since 1931, the UNI was transferred to the budget of the German Ministry of Education and became a public institution at the Friedrich-Wilhelm University in Berlin. An important part of the rich educational, publishing and research activity of the UNI were the courses (at three levels of language training) of the Ukrainian language for the students of Friedrich-Wilhelm University in Berlin, led by the linguist Dr. Zenon Kuzelia. In 1940, the UNI linguist Yaroslav Rudnyckyj, who in 1938 moved to Berlin from Lviv, published a textbook of the Ukrainian language for German students (subsequently reprinted four times). The textbook collected and systematized all the grammatical information about the Ukrainian language of the inter-war period, and covered various cultural aspects, as evidenced, in particular, by an interesting selection of folklore texts for reading or song texts. An important supplement to the book was a German-Ukrainian and Ukrainian-German dictionary, as well as a small terminological index. In 1945, with the approach of Soviet troops to Berlin, the UNI first moved to Leipzig and soon ceased to exist. Most of its staff moved to Munich, while a significant number emigrated to the United States, Canada, and Latin America. Key words: Ukrainian emigration in Germany, interwar period, Ukrainian Scientific Institute in Berlin, Ukrainian language, textbook of Ukrainian language, Zenon Kuzelia, Yaroslav Rudnyckyj.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".