Inveterate Voyager: J.B. Rudnyckyj on Ukrainian Culture, Books, and Libraries in the West During the “Long Cold War”
Bibliographic record
Abstract
This paper deals with J.B. Rudnyckyj (1910–1995), a leading Ukrainian émigré scholar of the Cold War period, and his manifold contributions to library science in Canada and the West in general. Although he was a philologist and lexicographer by training and profession, Rudnyckyj took a keen interest in all Ukrainian books and libraries to which he had access during this period. From his very immigration to Canada in 1949, he traveled extensively in this country, in the USA, and in Western Europe. Everywhere he went, he investigated local private Ukrainian, public, and academic libraries, museums, and cultural centres, met with resident scholars, both émigré and Western, and wrote about them in his voluminous publications. These included both travelogues with a strong cultural bent and also more formal library descriptions. For two decades he also compiled extensive yearly bibliographies of Slavic publications in Canada. Rudnyckyj’s motivation, it seems, was a desire to document and preserve the Ukrainian cultural heritage which he thought was under threat in his ancestral European homeland. Today, all this material forms a valuable resource for the history of Slavic studies in Canada during the time of the “Long Cold War” (1945–1991). It also says much about Ukrainian culture in North America in general during this period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.012 |
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".