Bibliographic record
Abstract
This book explores the multiplicity of women’s experiences in the Cambodian genocide during the four-year rule of the Khmer Rouge. The dominant discourses of genocide often speak from a patriarchal and national perspective, rendering women speechless, and yet in this volume, the female survivors of the Cambodian genocide testify not only to the specific atrocities committed during the war but also to the pre-war conditions that laid the groundwork for a gender-specific victimization of women and its continuation post-war. With the help of testimonies from Khmer women who joined the Khmer Rouge, women who experienced sexual violence during the Khmer Rouge era, women who fled the country, and the Cham women who faced expulsion from home, this book explores the diversity of women’s experiences under the Khmer Rouge. Survivors’ accounts show that a Khmer woman’s experience with the Khmer Rouge was considerably different from the experience of not only a Khmer man but also a woman from a religious or ethnic minority group or a woman who chose to join the Khmer Rouge. These differences are conveniently ignored in nationalist discourses in Cambodia and by western scholars of history and gender-based violence, and they are given even less consideration in discourses about women survivors in diaspora. Instead of forcing generalization and universalization of gendered crimes of war, Gender and Genocide in Cambodia employs feminist curiosity and closely examines women’s experiences under the Khmer Rouge from multiple vantage points. This volume is essential reading for students and scholars interested in gender and cultural studies, political history, and modern 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".