Bibliographic record
Abstract
In the spring of 1940 Canada sent hundreds of highly trained volunteers to serve in Britain's Royal Air Force as it began a concerted bombing campaign against Germany. Nearly half of them were killed or captured within a year. This is the story of one of those airmen, as told through his own letters and diaries as well as those of his family and friends. Joey Jacobson, a young Jewish man from Westmount on the Island of Montreal, trained as a navigator and bomb-aimer in Western Canada. On arriving in England he was assigned to No. 106 Squadron, a British unit tasked with the bombing of Germany. Joey Jacobson’s War tells, in his own words, why he enlisted, his understanding of strategy, tactics, and the effectiveness of the air war at its lowest point, how he responded to the inevitable battle stress, and how he became both a hopeful idealist and a seasoned airman. Jacobson's written legacy as a serviceman is impressive in scope and depth and provides a lively and intimate account of a Jewish Canadian's life in the air and on the ground, written in the intensity of the moment, unfiltered by the memoirist's reflection, revision, or hindsight. Accompanying excerpts from his father's diary show the maturation of the relationship between father and son in a dangerous time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".