Bibliographic record
Abstract
This volume presents women warriors and hero cults from a number of cultures since the early modern period. The first truly global study of women warriors, individual chapters examine figures such as Joan of Arc in Cairo, revenging daughters in Samurai Japan, a transgender Mexican revolutionary and WWII Chinese spies. Exploring issues of violence, gender fluidity, memory and nation-building, the authors discuss how these real or imagined female figures were constructed and deployed in different national and transnational contexts. Divided into four parts, they explore how women warriors and their stories were created, consider the issue of the violent woman, discuss how these female figures were gendered, and highlight the fate of women warriors who live on. The chapters illustrate the ways in which female fighters have figured in nation-building stories and in the ordering or re-ordering of gender politics, and give the history of women fighters a critical edge. Exploring women as military actors, women after war, and the strategic use of women’s stories in national narratives, this intellectually innovative volume provides the first global treatment of women warriors and their histories
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".