Food Will Win the War: The Politics, Culture, and Science of Food on Canada’s Home Front
Bibliographic record
Abstract
When most of us think of Canadian history, particularly Canada’s involvement in the Second World War, it is unlikely that food is what first comes to mind. However, Ian Mosby’s new—and first—book, Food Will Win the War: The Politics, Culture, and Science of Food on Canada’s Home Front, invites readers to consider the primacy of food in the war effort in Canada. Mosby’s detailed and thoroughly researched account explores food as a material and symbolic resource that was instrumental in marshalling Canadians’ support for the war. Mosby also shows how the social, political, and economic changes related to food shaped the everyday lives of Canadians—particularly Canadian women—throughout the Second World War. Food Will Win the War is an important volume that fills a significant gap in the small, but growing, literature on Canada’s food history.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.048 | 0.031 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".