Ukrainian Diaspora in Canada and Its Contribution to the Establishment of Independent Ukrainian State
Bibliographic record
Abstract
The history kept for us names of the first Ukrainian, arrived to Canada in 1891. These are residents of the village of Nebylov in the Western Ukraine Ivan Filippov and Vasily Elenyak. The Ukrainian immigration to Canada gains mass scope only after 1896, in many respects thanks to efforts of the galitsky agronomist Osip Oleskov who sent a big flow of the Ukrainian immigrants from villages of the Western Ukraine instead of Brazil to Canada. During the first wave of the Ukrainian immigration to Canada which is considered the largest and occurred between 1891 and 1914, in the country lodged more than 170 thousand Ukrainian. The second wave of Ukrainian immigration to Canada occurred in the interwar period, especially between 1924 and 1930. The third wave of Ukrainian immigration to Canada was due to political reasons and lasted from 1947 to 1954. Many of these immigrants were political refugees, which made this wave overtly politicized. In the early 1990s began the fourth wave of Ukrainian immigration to Canada, which continues today. This wave was related mainly to economic reasons.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".