Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the construction of gender identity in the Canadian television series Bomb Girls (2012-2013), which depicted the lives of women working at a munitions factory during the Second World War. Design/methodology/approach This research is guided by a postmodern feminist and historiographic approach to organization studies. The study involved a qualitative content analysis of the series to explore the construction of gender identity among female factory workers, given traditional social constructions of gender prominent in wartime. Findings In its (re)construction and (re)negotiation of gender identity, Bomb Girls told a story about women’s working lives during the Second World War that reflected themes of independence, resilience and transformation. Research limitations/implications This paper contends that Bomb Girls is a revisionist work of postmodern feminist history that subverts gender norms and retrospectively offers a nuanced and progressive narrative about the lives of Canadian women who entered the workforce during the Second World War. Originality/value This research contributes to historiographical approaches to management and organization studies by bringing a postmodern feminist historical lens to the study of women’s work in a popular culture representation. In doing so, this research responds to long-standing and widespread calls for an “historic turn” in the field as well as for research that addresses gender as a central analytical category.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".