Bibliographic record
Abstract
The article looks at Holocaust related death lists in the permanent exhibition of the Bergen-Belsen Memorial Museum. The museum opened to the general public in October of 2007. I argue that Holocaust lists are best understood as memorial objects which project a particular kind of aura. This aura also surrounds the sacral and criminal landscape of Bergen-Belsen, which the lists have come to represent and mediate. It is the relationship of list to landscape that structures their shared auratic resonances, in the interplay between presence (what is documented in the list) and absence (names that have been destroyed, never to be retrieved). In the case of the lists of Bergen-Belsen this is even more nuanced, in that there were two landscapes where the detritus of the genocide unfolded: the iconic mass graves of Belsen and the displaced persons camp, several kilometers down the road from the concentration camp, where the sick and dying were transported after the liberation. Given that there is no original list of the dead in the mass graves of the concentration camp, the death lists in the displaced persons camp take on a more complex memorial meaning. In conclusion, I make the argument that the memorial experience of Bergen-Belsen is a useful template from which to view other transnational sites of destruction and crimes against humanity.
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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 | 0.010 | 0.021 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".