From the Front to the West Coast : the Recollections of the Finnish War Veterans in Vancouver
Bibliographic record
Abstract
This is a story of a country, Finland, at war as told through the experiences of veterans. The book starts off with the Winter War, and continues on to the two other wars that followed, revealing history through personal experience as well as the consequences to the country as a whole; tragedy and hope. However, after the war, these veterans left the country they had so fiercely defended to start a new life in Canada. This unique project, a historical snapshot, searches for answers as to why they left Finland for Canada. Did the wars influence their decision? Despite the seriousness of the topic, sprinklings of humour in the stories lighten the mood. ”From the Front to the West Coast is a cultural achievement, because it attests the vitality of memories from decade to decade. The documentary is a reminder of how the memories of where you lived during childhood and youth endure forever in the human mind. It is amazing to witness the significance of being Finnish, and the significance of war memories, for these veterans.” — Mika Kulju, Finnish historian and non-fiction author of Frozen Hell – The Legend and the Tragedy of Raate Road.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.046 | 0.006 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".