Regulating Body Boundaries and Health during the Second World War: Nationalist Discourse, Media Representations and the Experiences of Canadian Women War Workers
Bibliographic record
Abstract
This article examines the intersections of gender, wartime nationalist rhetoric and the production of ‘healthy’ and ‘unhealthy’ bodies in both the Canadian workplace and the home during the Second World War. Analysing government, industry and media discourses in relation to oral history interviews with thirty‐eight women aircraft workers, we discuss women's distinctive role in shaping the health and morale of the social body during wartime, to ensure the maintenance of family, nation and the Allied war effort. While health in wartime was defined in terms of worker productivity for both men and women, anxiety about women's expanded roles heightened the emphasis on moral respectability as a marker of the ‘healthy’ female body. This was further complicated by the wartime emphasis on women's responsibilities to boost morale as part of their role in maintaining health and productivity for both men and women. Through such examples as workplace regulations and domestic advice, we examine the increased monitoring of women's individual and collective bodies and the intensified demands on female war workers as they crossed between the public and private spheres. We use our oral histories to examine women's embodied memories of ‘healthy’ and ‘unhealthy’ bodies within a regional context and their responses to government, industry and media discourses.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.047 | 0.042 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".