Women in the Margins: Media Representations of Women's Labour in the Canadian Press, 1935-1945
Bibliographic record
Abstract
During the Second World War, women’s participation in Canada’s ‘total war’ effort meant increased domestic responsibilities, volunteering, enlisting in the armed forces, and joining the civilian workforce. Women’s labour force participation more than doubled throughout the war, with more women working alongside and in place of men than ever before. This created a situation that could challenge the traditional sexual division of labour, and so women’s labour became a subject for discussion in the public sphere. Through a comparative content analysis of the commercial and alternative (labour) press, this study examines representations of women’s labour in wartime in the context of women’s mobilization into the war effort through to subsequent demobilization near war’s end. It first considers the theoretical and methodological issues involved in the historical study of news media and women and then offers original empirical research to demonstrate that when women’s labour did emerge as a subject in the Canadian press, gender, not labour, was prioritized in the news. This was symbolically and systematically leveraged both within and across the commercial and alternative press, which reinforces stereotypical values about women and their labour and upheld the patriarchal status quo. In the end, while there were surface-level changes to the nature of women’s paid labour during the war, the structures of female subordination and exploitation remained unchallenged despite women’s massive mobilization into the workforce. By setting media representations against the wartime realities of women’s labour told through archival records and secondary literature, this dissertation argues that news media generally presented a ‘history’ of women’s labour that did not reflect the lived reality or the political economic and social significance of women’s labouring lives. This not only coloured how women’s labour was represented in the news, but it can also shape the history that scholars construct from the newspaper. In contributing to feminist media and media history scholarship, this dissertation offers empirical evidence that challenges dominant ways of thinking about women’s history in terms of the domestic sphere and furthers an understanding of women’s wage labour as a provocation to such historical public-private divisions. This may, in turn, inspire histories that more fully and equitably capture women’s experiences.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.025 | 0.012 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".