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Moving Pictures at the Edge of Stasis

2012· book-chapter· en· W2662460183 on OpenAlexaff
Paul Coates

Bibliographic record

VenueOxford University Press eBooks · 2012
Typebook-chapter
Languageen
FieldArts and Humanities
TopicPolish-Jewish Holocaust Memory Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsElegyLiteratureElegiacArtDramaPoetry

Abstract

fetched live from OpenAlex

Abstract This article addresses elegy in film. Although Totem and Taboo does not mention elegy explicitly, Sigmund Freud's remarks on the remorse and tenderness a band of brothers feel for the patriarch of the primal horde after murdering him allow one to surmise that he would have considered the first elegy to be motivated. Although cinema is shot through with elegiac moments, it contains very few films classifiable generically as elegies. Voiceover and the drama of the future are impregnated with elegy. Music is one of the key distancing devices film employs to elegiac ends. Claude Lanzmann's Shoah meditates upon the near-annihilation of the Jews in the concentration camps of the National Socialists as the final stage in a gradual process of anti-Semitic exclusion originating deep in the darkest recesses of European history. Maciej Drygas' film stands in a tradition for which elegy can represent indictment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.207
Teacher spread0.154 · 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
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
Published2012
Admission routes1
Has abstractyes

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