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Record W2940839843 · doi:10.1111/gequ.12103

Collective Emotions and Victimization in the World War Two Film<i>Der Untergang</i>(2004)

2019· article· en· W2940839843 on OpenAlexaff
Jan Süselbeck

Bibliographic record

VenueThe German Quarterly · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Emotions Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEmotiveHistoryGermanLiteratureAestheticsArt historyArtSociologyAnthropology

Abstract

fetched live from OpenAlex

After Bernd Eichinger's blockbuster war movieDer Untergangwas released in 2004, it received many positive reviews by North‐American critics. But the biggest success of this film is still on‐going: more than a decade later,Der Unterganghas become canonized in a way similar to the Oscar winning GDR surveillance movieDas Leben der Anderen(2006). Today,Der Untergangis one of the classic films to teach the “Third Reich” in many German courses. While many scholarly studies have been written aboutDer Untergang, they do not use the most promising methodological approach that can help us to understand how this film manages to be so suggestive. This paper's thesis is that it is crucial to take a closer look at the emotive strategies used inDer Untergang. Emotion research is the key to understanding the film's transnational success.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.003
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 head0.020
GPT teacher head0.267
Teacher spread0.247 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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