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Record W3134129834

Speaking for the Dead: The Memorial Politics of Genocide in Namibia and Germany

2017· article· en· W3134129834 on OpenAlexaff
Ronald Niezen

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Colonialism and Identity Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGenocideThe HolocaustPoliticsGermanDissentPolitical scienceLawState (computer science)Resistance (ecology)MemorializationCriminologySociologyHistoryArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the politics of the material commemoration of mass crime, with a focus on the Ovaherero and Nama descendants of the victims of a 1904-1908 mass ethnic killing in German Southwest Africa. My approach to monuments emphasises their place as constitutional artefacts that mark changes of regime after war or revolution, and as focal points of resistance to state regimes of commemoration. Tracing the material forms of memorialization in Germany reveals the significance of both a “remembrance culture” of the Holocaust and, at the same time, resistance to recognition of the Ovaherero/Nama genocide. In Namibia, the success of the Ovaherero/Nama activist campaign in Germany prompted the government to shift positions and take up the cause of genocide remembrance, asking Germany to officially recognize that its actions constituted genocide, to issue a formal apology and to pay reparations. The study of the Herero/Nama activist campaigns in Namibia and Germany thus reveals the ways that activists were able to translate and repurpose genocide claims by crossing into different geographies of commemoration and dissent and returning with new tools for leveraging politics at home.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.262
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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