Creating a “Vocabulary of Rupture” Following WWII Sexual Violence in Hungarian Women Writers’ Narratives
Bibliographic record
Abstract
In this paper, Schwartz analyses three narratives by Hungarian women writers— Alaine Polcz’s Asszony a fronton (A Wartime Memoir), Judit Kováts’s Megtagadva [‘Denied’] and Fanni Gyarmati Miklósné Radnóti’s Napló [‘Diary’]—with regard to their representation of the rapes of Hungarian women by Red Army soldiers during WWII. Schwartz examines to what degree the rapes are positioned as a “rupture” in the first person narrators’ lives, and how the three narratives offer elements of a “vocabulary of rupture” (Butalia 2000) so as to work through traumatic memory and thus come to terms with both the short-term and long-term effects of trauma and social stigmatization. Even though the narratives eschew a black-and-white portrayal of the rapists, an orientalist stereotying is nonetheless present. Schwartz concludes with Avery Gordon that these and other rape narratives can be read as part of the process of settling the ghosts of a still unresolved past violence yet beyond simple ideological binaries along the victim-perpetrator line.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".