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Record W4318982864 · doi:10.54145/actamn.59.06

Hitlerjugend Waffen-SS Division. Faces of Fanaticism

2023· article· en· W4318982864 on OpenAlexaboutno aff

Bibliographic record

VenueActa Musei Napocensis Historica · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsnot available
FundersMagyar Tudományos Akadémia
KeywordsFanaticismBattleEliteOfficerDisengagement theoryLawSociologyPolitical scienceHistoryAncient historyPoliticsMedicine

Abstract

fetched live from OpenAlex

Research into the different types of fanaticism that animated some of the most notorious elite forces of the Third Reich represents a key investigation tool for any historian who applies hermeneutic and phenomenological criticism of combat motivation and morale among warriors belonging to Waffen‑SS troops. The study below addresses the very specific features of the ordinary fighter conscripted to the 12th SS Panzer Division ‘Hitlerjugend.’ The fierce battles that compounded the Normandy Campaign (also known as Operation Overlord) of June – August 1944 were particularly shaped by the committed and uniquely involved units belonging to the Hitlerjugend Division, alternatively called the Baby Division by their Canadian, Australian and British opponents. These youngsters had been battle‑hardened before their ‘fire‑baptism’ due to a tough and professionally delivered military and propagandistic program aimed at transforming young soldiers into efficient killing machines, sufficiently indoctrinated so that they could perform outstanding duties through morale disengagement under contextual forces. Both theoretical and military training were delivered by a professional officer’s corps, assisted by NCO’s formed of veterans with a long battle experience on the Eastern Front. Cross investigation analyses were conducted with the purpose of gaining a complex view and better understanding of all social, psychological and military mechanisms that worked together in order to obtain Hitler’s ultimate warrior: ‘the Hitlerjugend soldier.’

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.526
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.051
GPT teacher head0.306
Teacher spread0.255 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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