Bibliographic record
Abstract
Canada was not in a welcoming mood when Ukrainian Displaced Persons and other refugees began immigrating after the Second World War. In this compelling and richly documented account, Lubomyr Y. Luciuk maps the established Ukrainian Canadian community's efforts to rescue and resettle refugees, despite public indifference and the hostility of political opponents in Canada and abroad. He explores the often divisive impact that this 'third wave' of nationalistic refugees had on organized Ukrainian Canadian society, and traces how this diaspora's experiences of persecution under the Soviet and Nazi regimes in occupied Ukraine, and their subsequent hiving together in the cauldrons of the postwar DP camps, underlay the shaping of a shared political world-view that would not abate, despite decades in exile. Drawing on personal diaries, in-depth interviews, and previously unmined government archives, the author provides an interpretation of the Ukrainian experience in Canada that is both illuminating and controversial, scholarly and intimate. Skilfully, Luciuk reveals how a distinct Ukrainian Canadian identity emerged and has been manipulated, negotiated, and recast from the beginnings of Ukrainian pioneer settlement at the turn of the last century to the present. Written with journalistic skill and a clear interpretive vision, Searching for Place represents a meticulous, original, and provocative contribution to the study of modern Canada and one of its most important communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.887 | 0.709 |
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".