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Record W2516015100 · doi:10.7202/1037005ar

Hitler, un film d’Allemagne, une machine de mémoire. Spatialité de l’art du deuil

2016· article· fr· W2516015100 on OpenAlexvenueno aff
Lucie Picandet

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicDeath, Funerary Practices, and Mourning
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article propose une lecture poétique du processus psychique de deuil engagé dans Hitler, un film d’Allemagne ( Hitler, ein Film aus Deutschland , 1977), de Hans Jürgen Syberberg, et tente de fournir une clé d’interprétation esthétique à cette oeuvre singulière en confrontant les dispositifs d’espace et de temps du film à ceux des arts de la mémoire. En s’appuyant sur ces pratiques mnémoniques qui visent à structurer la pensée par les « images » ( imagines ) et les « lieux » ( loci ) de la mémoire, l’auteure interroge la dimension artistique du deuil chez Syberberg, à travers trois exemples qui révèlent une progression dans les opérations de mutation psychique de l’image de Hitler. Quelle(s) forme(s) et fonction(s) le dispositif filmique prend-il dans ces opérations de spatialisation et de mécanisation de la mémoire et de l’oubli propres au travail du deuil ?

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.264
Teacher spread0.243 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

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