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Record W2947090784 · doi:10.31124/advance.8115953.v1

Askari at Hitler’s Frontier:Racial-Cultural Chauvinism and Colonial Systems in Germany and the Territories of the Eastern Front, 1941-1945

2019· preprint· en· W2947090784 on OpenAlexaffabout
Drew Eisenberg-Holmes

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGermanChauvinismColonialismFront (military)FrontierSlavic languagesStyle (visual arts)HistoryRacismSociologyPolitical scienceClassicsGender studiesGeographyLawPoliticsArchaeology

Abstract

fetched live from OpenAlex

This is a paper written for the University of Toronto and adheres to it’s standards. It was written and formatted in Chicago 17th style and uses written and digital scholarly and published sources. One source is the author’s own translation of a German text. Otherwise, widely accepted English translations are used (i.e. original English translation of “Mein Kampf”). This paper covers the interrelationship between German colonial thought and German / non-German relationships on the Eastern Front during the Second World War, particularly relations with collaborationist states and Slavic volunteers to the Waffen SS.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.191
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.006
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes2
Has abstractyes

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