MétaCan
Menu
Back to cohort
Record W2942297143 · doi:10.5038/1911-9933.13.1.1584

Raphaël Lemkin’s Derivation of Genocide from His Analysis of Nazi-Occupied Europe

2019· article· en· W2942297143 on OpenAlexvenueno aff
Raffael Scheck

Bibliographic record

VenueGenocide Studies and Prevention · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideNazismLawGermanNazi GermanyPolitical scienceWorld War IISociologyHistoryPolitics

Abstract

fetched live from OpenAlex

The breadth and complexity of Lemkin’s definition of “genocide” results from several influences during the time he developed the concept. One of them is a belief that Nazi Germany was engineering a demographic revolution that would leave Germany predominant in Europe regardless of the outcome of the military conflict. This notion facilitated the assumption of a coherent cynical motivation behind disparate policies, laws, and decrees. Second, Lemkin’s daily work for the U.S. Government reinforced his focus on economic and legal matters and helps to explain why they occupy such a prominent place in his book Axis Rule. His job provided Lemkin with good access to information and encouraged a detailed analysis of Nazi occupation techniques, but it prioritized economic exploitation over atrocities, with a view to restitution after the liberation of the occupied territories. Third, Lemkin’s strong focus on the law and his belief in the curative effect of law, although already evident before the war, was reinforced by his desire to prove German violations to a hesitant American public and by his hope to contribute to a legal condemnation of genocide in all of its forms after the war. This focus favored Nazi violations of international law that could be proven through legal texts and therefore led to a broad definition of genocidal acts while obscuring the most heinous crimes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.336
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.262
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGenocide Studies and PreventionSame topicHistorical and Contemporary Political DynamicsFrench-language works237,207