Bibliographic record
Abstract
Soviet Karelia in the Life Writing of Finnish North AmericansIn the early 1930s, approximately 6,500 Finns from Canada and the United States moved to Soviet Karelia, on the border of Finland, to build a Finnish workers' society.They were recruited by the Soviet leadership for their North American mechanical and lumber expertise, their familiarity with the socialist cause, and their Finnish language and ethnicity.By 1936, however, Finnish culture and language came under attack and ethnic Finns became the region's primary targets in the Stalinist Great Terror.Building That Bright Future relies on the personal letters and memoirs of these Finnish migrants to build a history of everyday life during a transitional period for both North American socialism and Soviet policy.Highlighting the voices of men, women, and children, the book follows the migrants from North America to the Soviet Union, providing vivid descriptions of daily life.Samira Saramo brings readers into personal contact with Finnish North Americans and their complex and intimate negotiations of self and belonging.Through letters and memoirs, Building That Bright Future explores the multiple strategies these migrants used to make sense of their rapidly shifting positions in the Soviet hierarchy and the relationships that rooted them to multiple places and times.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.515 | 0.248 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".