Fellow Traveller: A British Columbia Fisherman Writes Home from the Eastern Bloc, 1952
Bibliographic record
Abstract
In autumn 1952, fisherman Elgin “Scotty” Neish travelled through Eastern Europe en route to the Asia and Pacific Rim Peace Conference in Beijing, China. A member of the Labor-Progressive Party (lpp), as the Communist Party was then called, Neish penned letters home during his seven week trip for publication in The Fisherman, the newspaper of the United Fishermen and Allied Workers’ Union (ufawu). These letters provide a unique window into the perspective of a radical British Columbia trade unionist at the height of the Cold War and touch on diverse global themes. Elgin Neish was a salmon troller who had helped organize the ufawu during World War II. The son of Scottish immigrants, he grew up in the squatter colony of Deadman’s Island, off Vancouver’s Stanley Park. After civic authorities evicted the squatter families in the early 1930s, Neish left school at age eleven to join his father and brothers fishing aboard the home-made skiff Lindmore Lass. He was a war veteran, serving in the “Gumboot Navy,” the armada of British Columbia fishers that guarded the coast against Japanese U-boat attack.1 After the war, Neish belonged to the “militant minority” that challenged the assumptions and practices of the Cold War, as McCarthyism enveloped North American political culture and British Columbia’s “Red” unions came under siege.2 According to a Vancouver Province expose, the
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".