Legal and Social Aspects of the Belarusian Economic Emigration to Canada in the 1920s-30s
Bibliographic record
Abstract
The author examines the main features for the formation of the Belarusian economic emigration to Canada. The intensity of the emigration from 1921 to 1939 was analyzed, when the territory of Western Belarus was a part of Poland. The historical base of the research was the unpublished documents of the Belarusian, Ukrainian and Polish archives. The article presents the structure of state emigration bodies that were involved in organizing and controlling the recruitment of emigrants, their employment and the process of re-emigration. It describes the features of the Canadian legislation for the scale of the Belarusian emigration and the legal adaptation of emigrants. Particular attention is paid to the role of the Canadian railway companies “Canadian National Railways” and “Canadian Pacific Railways” in the selection of emigrants and their employment in agriculture and industry. The author argue that the Polish authorities stimulated the emigration of the Belarusian population for the polonization of Western Belarus. The problematic socio-psychological adaptation of the Belarusian emigrants, because Belarusians in Canada weakly expressed the national identity, is described. The author concludes that the international cooperation had an important role in forming the diaspora’s and national identity, especially the international contacts with the representatives of other peoples and the participation in common political organizations and projects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".