From Victim Hierarchies to Memorial Networks: Berlinâs Holocaust Memorial to Sinti and Roma Victims of National Socialism
Bibliographic record
Abstract
In April 1989, four months after a German citizens’ initiative proposed construction of a central memorial to the Jewish victims of the Holocaust, Romani Rose, chair of the Central Council of German Sinti and Roma, published a petition demanding inclusion of the Sinti and Roma victims into the same memorial. Any other outcome, he wrote, would indicate a “hierarchy of victims” (die Zeit). The Berlin Wall fell seven months later, transforming the political and spatial dimensions of Germany’s commemorative landscape. So began a new phase of contestation – a national memorial project at its centre – over the so-called uniqueness of the (Jewish) Holocaust, and the moral and political responsibility of the newly reunified German state for genocide committed against Jewish and “other” victim groups. \nThis dissertation draws on an entangled understanding of memory production in order to disentangle the social relations and identities that are mobilized in national memorial projects. I define entangled memory in two ways: (1) it refers to the interlinking of dominant memory and oppositional forms in the public sphere (Popular Memory Group 1998); (2) it is multidirectional in that the subjects and spaces of public memory are defined not only by a competition of victimhood but also as a product of influence and exchange (Rothberg 2009). This framework allows me to argue that the genocide of the Sinti and Roma – historically forgotten victims – is gradually gaining a foothold in the German national imaginary via the dominant status of the memorial to the Jewish victims. In turn, the positioning of the memorial dedicated to Jewish victims has been and continues to be influenced by the commemorative activities of other victim groups. German state legislation in 2009 to link up the memorials dedicated to Jewish, Sinti and Roma as well as homosexual victims – the country’s three national memorials – under one administrative roof is a recent example of an emergent memorial network in the country’s commemorative politics. It is here, I conclude, in the New Berlin’s geographic, symbolic, virtual and cartographic spaces of national memory that we are seeing increasing forms of recognition and integration of historically marginalized groups.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".