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Record W2046930538 · doi:10.3138/md.52.2.192

The Feast of Nemesis Media: Jean Cocteau's <i>The Eiffel Tower Wedding Party</i>

2009· article· en· W2046930538 on OpenAlexvenueno aff
Allan Pero

Bibliographic record

VenueModern Drama · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicCinema History and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)AestheticsWitnessBELLAArtEvent (particle physics)LiteratureSymbol (formal)HistoryLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

Jean Cocteau's The Eiffel Tower Wedding Party is marked by a fascination with the fractious relationship both between technology and theatricality and between human desire and mechanization. In its anti-theatricality, the play shifts away from reproduction with a greater fidelity to “life,” or the theatrical representation of life, toward the assumptions that inform the desire for photographic reproduction. Eschewing banal hypotheses like “machines are dehumanizing,” Cocteau suggests a more complex desire: we want machines to exert control over the moment of the live event. His use of machines uncannily shows us that we exalt the representation of the event over its emotional content. What Cocteau is asking us to witness, then, in his exploration of our relationship to media, is a creative process inherent in the destruction of theatricality. In Walter Benjamin's terms, one could argue that the play is a significant moment in the ongoing decay and transformation of theatricality's aura.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.004
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.218
Teacher spread0.197 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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