‘I Still Struggle to Ensure that I am Truly Listening': Understanding Gender, Sexuality, and Sexual Violence During the Holocaust. A Conversation
Bibliographic record
Abstract
While perspectives on gendered and sexual experiences, practices, and norms during the Holocaust have significantly changed in recent decades, questions remain about how to understand and represent these topics, particularly gender-based and sexual violence. In this conversation, six Holocaust scholars, from varied backgrounds and representing different generations, respond to questions posed by the special issue editors, Dorota Glowacka and Regina Mühlhäuser. They discuss the current state of debates about gender, sexuality, and sexual violence during the Holocaust. Reflecting on the material conditions and distinguishable geographical and ideological coordinates in which they have conducted their work, they recount ideas and scholarly currents that have helped them generate their specific modes of understanding. They consider the challenges and obstacles to knowledge production they have faced at various stages of their work, revealing how ingrained assumptions about gender and sexuality circumscribe research questions, methods of inquiry, and the ways in which their findings are interpreted, presented, and received. While they address the impact of changing social sensibilities and perceptions of gender and sexuality on their work and point to the emergence of new themes and areas of study, they also draw attention to the subjects that remain unexamined, socially sanctioned, or excluded from rigorous examination.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.071 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 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".