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Record W2997900658 · doi:10.33137/q.i..v38i1.31161

Vladimir Mayakovsky as Exemplary Character: Two Interpretations by Dario Fo and Carmelo Bene

2018· article· en· W2997900658 on OpenAlexvenueno aff
Malcolm Angelucci, Stephen Kolsky

Bibliographic record

VenueQuaderni d italianistica · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicItalian Literature and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryCharacter (mathematics)Rhetorical questionArtLiteratureFraming (construction)Context (archaeology)Performing artsPoliticsHumanitiesHistoryPolitical scienceLawMathematics

Abstract

fetched live from OpenAlex

This article contributes to the mapping of the role played by the Russian poet, playwright, artist and performer Vladimir Mayakovsky (1893-1930) in the Italian context of the 60s and 70s, concentrating on Dario Fo’s L’operaio conosce 300 parole, il padrone 1000, per questo lui è il padrone (1969), and Carmelo Bene’s TV production of Bene! Quattro modi di morire in versi (1974, broadcast in 1978). Mayakovsky appears here as a character, constructed as an exemplary figure for the role of the artist. After framing exemplarity theoretically as a strategy that effaces the intrinsic discrepancy between example and rule, the article will map the presence of this rhetorical move in the two texts. It will discuss the ways in which they share a series of common features, forming in both cases an implicit agenda of legitimization at a time when both Fo and Bene were shifting the context of their practice. In this sense, this contribution argues that Fo’s L’operaio and Bene’s Quattro modi both introduce a programmatic element that defines a specific poetic and politics, and at the same time attempt at performing the very poetic that is being presented.

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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.816
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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.002

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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
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
Published2018
Admission routes1
Has abstractyes

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