Bibliographic record
Abstract
In Vielleicht Esther (2014), the literary debut by Ukrainian-born Katja Petrowskaja, the narrator attempts to trace her family history. She realizes that she can no longer rely on the memories of her relatives, but rather, as part of what Marianne Hirsch calls the “generation of postmemory,” is dependent on the material that remains. She encounters various archive spaces and resources, but these fail to provide easy access to her family’s past. This article argues that Vielleicht Esther is thus a pivotal example of an archival turn in memory culture, which signals not only the central position of the archive in retracing the past, but also the increasing critical scrutiny of the status and role of archive in this endeavour. Petrowskaja’s narrator comes to see how the archive is implicated in the control of history and memory, and that what remains is also an indicator of what is missing – specifically the European Jewish tradition that once defined her ancestors. Moreover, the archive confronts her not only with what remains (and what doesn’t), but also with questions about who remains (and why), that is, with questions about the circumstances of survival. On the one hand, her encounters with the archive allow her to address its gaps through narrative, but on the other, they confront her with unpalatable truths that force her to rethink her family narrative.
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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 | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".