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Record W4367157341 · doi:10.7202/1091836ar

Hear the Machine, Fear the Machine: George Antheil’s Ballet Mécanique and Listener Ambivalence in the Twentieth Century

2022· article· en· W4367157341 on OpenAlexvenueno aff
Carolyne Sumner

Bibliographic record

VenueIntersections Canadian Journal of Music · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
FundersJohns Hopkins UniversityUniversity of Minnesota
KeywordsBalletAmbivalenceGeorge (robot)PianoArtFirthArt historyVisual artsPsychologyPsychoanalysisDance

Abstract

fetched live from OpenAlex

George Antheil’s Ballet Mécanique is notorious for its cacophonous sonorities, its industrial allusions, and its use of mechanical instruments, notably the player piano. Despite a successful première in Paris in 1926, the 1927 American reception of the piece was viscerally critical. Drawing upon contemporary documents, this article reconsiders the American reception of the ballet in light of the relationship between early twentieth-century American audiences and the mechanical. It suggests that through its use of mechanized instruments, specifically the player piano, Ballet Mécanique exacerbated anxiety and skepticism about the mechanical and mirrored a growing fear about the destructive consequences of a mechanized society.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.017
Scholarly communication0.0080.002
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.020
GPT teacher head0.207
Teacher spread0.187 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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