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Record W4367157401 · doi:10.7202/1091837ar

Machines, Films, and Operas: A (Mostly) Soviet Perspective

2022· article· en· W4367157401 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueIntersections Canadian Journal of Music · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsCanadian University Music Society
Fundersnot available
KeywordsOperaFuturistCultCriticismBalletSoviet unionModernityPerspective (graphical)ArtLiteratureArt historyAestheticsHistoryVisual artsPhilosophyEpistemologyPolitical scienceLawDance

Abstract

fetched live from OpenAlex

In this article I explore some of the ways in which opera was affected by the dynamics of rupture and experimentation in the Soviet Union in the 1920s and early 1930s. In particular, I examine the criticism of opera as a genre among composers and theatrical practitioners, such as Nikolay Foregger, who advocated a fusion of opera and ballet inspired by the rhythms, movements, and sounds of modernity, and Adrian Piotrovsky, who argued for the transfer of cinematic devices to other art forms, including opera. The article further explores some intersections with the Futurist and Constructivist cult of the machine as reflected in the operatic experiments of Vladimir Deshevov and Aleksandr Mosolov, which were almost immediately suppressed by the rise of a more populist aesthetics and remain largely unknown.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.213
Teacher spread0.186 · 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