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Record W2501887240 · doi:10.1057/9780230618541_5

Putting the East in Order: German Historians and Their Attempts to Rationalize German Eastward Expansion during the 1930s and 1940s

2009· book-chapter· en· W2501887240 on OpenAlexaff
Eduard Mühle

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsIdeologyGermanPoliticsPower (physics)NazismSocialismOrder (exchange)Political scienceAestheticsSociologyMedia studiesLawHistoryArtCommunism

Abstract

fetched live from OpenAlex

I an Kershaw in his landmark biography of Adolf Hitler coined an interesting phrase when he put in a nutshell what made National Socialism function: “Working towards the Führer .” Hitler, once in power, did not—as Kershaw argues—have to give orders to let National Socialism take shape. The deeds and actions that made up the Third Reich were to a large extent performed voluntarily, on their instigator’s initiative. Hundreds of thousands if not millions of Germans tried to anticipate what they expected the Führer would wish without awaiting instructions from above. Hitler’s power, therefore, has to be understood as a social product, a creation of social and—we may add to Kershaw—national-patriotic motivations vested in Hitler by his followers. They hoped that their own interests and aspirations, which they pursued in their respective spheres of life, would be identical with those of the Führer . By trying to realize their own political and social hopes they translated the Dictator’s loosely framed ideological goals into reality by initiatives focused on working toward the fulfilment of Hitler’s visionary aims. 1 Another leading specialist in the field, Hans Mommsen, recently claimed that one should not speak of affinity when talking about people who shared only certain aspects of National Socialist politics and ideology, since this would unduly distance them from National Socialism. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0070.028
Scholarly communication0.0100.009
Open science0.0010.004
Research integrity0.0030.003
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 head0.258
Teacher spread0.237 · 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 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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venuePalgrave Macmillan US eBooksSame topicEuropean history and politicsFrench-language works237,207