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Record W4284991326 · doi:10.5038/1911-9933.16.1.1897

Dossier: The Hunger Plan: The Holocaust, Resource Scarcity, and Preventing Genocide in a Changing Climate

2022· article· en· W4284991326 on OpenAlexvenueno aff
Emily Sample

Bibliographic record

VenueGenocide Studies and Prevention · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideThe HolocaustNazismScapegoatScarcityRhetoricJudaismSociologyContext (archaeology)Political scienceLawHistoryEconomicsPolitics

Abstract

fetched live from OpenAlex

Nazi leadership sought to exploit the biological fear of starvation and scapegoat the Jewish population and other “useless eaters” for taking more than their fair share. The Nazis utilized and hyperbolized well-known prejudices against Jewish people, and entrenched narratives of Jewish parasitism as a threat to current and future German lives. In this analysis, food scarcity was one of several reasons for the Holocaust, and the first step to seeking Lebensraum for pure Germans to live to the highest international standard. This article will focus on different aspects of the complex antisemitic rhetoric surrounding issues of resource scarcity, including Hitler’s concept of Lebensraum , the ways in which the Nazi party discussed and understood food, food security, and the memory of World War I, as well as how that rhetoric influenced their policies, including Herbert Backe’s Hunger Plan. This analysis presents the so-called Final Solution as an answer to not only the Nazi’s Jewish problem, but a key aspect to their food security plans as well. Placing this analysis in the context of genocide prevention, the increasing insecurity and pressures climate change places on natural resources must be acknowledged as a trigger for future genocides.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.001
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 head0.113
GPT teacher head0.428
Teacher spread0.315 · 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 designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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