Bibliographic record
Abstract
Abstract This article explores the transformation in the levels of violence against women and children in Lebanon during the 1975–1990 civil war and the systematic atrocities committed, compared to the nineteenth-century where non-combatants were generally spared. Focusing on the 1982 Sabra and Shatila massacre, it analyzes how Lebanese fascist militias employed rape and mass killings as political tools to avenge military losses, reinforce ethno-nationalist dominance, and reclaim perceived lost masculinity. The Israeli military orchestrated these acts to impose collective punishment and psychological terror on Palestinians, while Lebanese leftists later exploited the massacre to reignite political mobilization. Existing scholarship has overlooked women’s experiences in civil wars, particularly in Lebanon, where narratives center on male combatants. This study fills this gap by examining how the modern Lebanese state dismantled traditional safeguards, exposing women and children to wartime violence. While women exercised agency through survival tactics and even militant roles, their actions were often tied to survival rather than feminist empowerment. By centering gendered violence in the analysis of war, this research challenges historiographical silences and re-positions women’s experiences within broader discussions of nationalism, trauma, and memory.
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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 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".