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IN POSSESSION OF A STOLEN WEAPON: FROM JOHN GAY’S MACHEATH TO RUBÉN BLADES’ PEDRO NAVAJA

2012· article· en· W2328975929 on OpenAlexvenueno aff
Antonio Viselli

Bibliographic record

VenueImaginations Journal of Cross-Cultural Image Studies · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)OperaPossession (linguistics)LiteratureArtHEROPerformance artSign (mathematics)CultHistoryArt historyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This article analyses the cult salsa song “Pedro Navaja” by Panamanian artist Rubén Blades and the relevance of narrating such a genre peculiar to dancing, an analysis in accordance with adaptation theory outlined by Linda Hutcheon, and a Brechtian semiotic methodology which combinesGestus with theories of the sign. “Pedro Navaja” is arguably a re-writing of “Mack the Knife” – or Die Moritat von Mackie Messer – one which contains, as a sort of mise-en-abyme, elements not only of Kurt Weill’s song, but of both John Gay’s The Beggar’s Opera and Bertolt Brecht’s The Threepenny Opera. This study focuses on the fertile adaptation history of the highwayman Macheath since Gay’s work, on close-readings of “Pedro Navaja” – a narrativized cerebral salsa song – and on the ethics of adapting a character, story or genre. Finally, when the character Pedro Navaja is adapted from Blades’ song by a cineaste and playwright, Blades, furious with what others have done with ‘his’ character, decides to resuscitate his eponymous hero killed off at the end of the original song in order to regain the authority of his creation. From theoretical questions including how to read an adaptation or what constitutes an adaptation, this article focuses on the diachronic recurrences of a specific character-type, on the significance of juxtaposing particular historical junctures and on the violence of adaptation and authorship.

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 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 score0.800
Threshold uncertainty score0.649

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 studies0.0000.002
Scholarly communication0.0000.009
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.399
Teacher spread0.338 · 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 teacher head, 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueImaginations Journal of Cross-Cultural Image StudiesSame topicTheater, Performance, and Music HistoryFrench-language works237,207