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Record W4394519198 · doi:10.6084/m9.figshare.22568612

Buñuel’s Messy Law and the “Extimate” Image in <i>El ángel exterminador</i> and <i>La Mort en ce jardin</i>

2023· dataset· en· W4394519198 on OpenAlexaff
David Campbell

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldArts and Humanities
TopicCinema History and Criticism
Canadian institutionsWestern University
Fundersnot available
KeywordsArtHumanitiesArt history

Abstract

fetched live from OpenAlex

Luis Buñuel’s notable Mexican film <i>El ángel exterminador</i> (1962) and his less familiar Mexican–French film <i>La Mort en ce jardin</i> (1956) coincide in their interest in portraying overbearing spaces of entrapment within which customs and rules of order reach points of exhaustion. With readings informed by elements of Lacanian thought, this paper explores the emergence of a messy, defective law and its implications for the mediatory qualities of language and the experience of subjectivity. I begin by arguing that the films make use of failures in communication to disrupt the paternal myth and the law of the signifier as these concepts are discussed in Lacanian thought. I then examine how these same disorienting forces also affect the imaginary support of the unified subject: Buñuel’s camera often reduces the prefigured image of subjects into piecemeal assemblages of partial objects or blends these images with surroundings. This paper concludes with a discussion of how <i>El ángel</i> generates visual lacunae that respond to this disorder. Unlike in <i>La Mort</i>, which portrays an authority that attempts to impose order in response to these gaps, <i>El ángel</i> produces sense <i>through</i> them, in a function understood by the term “extimacy.” This concept describes a foundation that is simultaneously intimate and exterior, and it is crucial to affirm the singularity of the subject before the mechanical operations of the signifier.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0350.002

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 head0.270
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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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