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Record W2188159167 · doi:10.1215/22011919-3614935

Refining<i>Uranium</i>: Bob Wiseman's Ecomusicological Puppetry

2014· article· en· W2188159167 on OpenAlexaff
Andrew Mark

Bibliographic record

VenueEnvironmental Humanities · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsYork University
Fundersnot available
KeywordsNarrativeComedyMusicalConsciousnessBridge (graph theory)The artsArtContent (measure theory)LiteratureEthnographyPerforming artsAestheticsVisual artsSociologyPhilosophyEpistemologyAnthropology

Abstract

fetched live from OpenAlex

Abstract This paper describes Bob Wiseman's allegorical piece, Uranium, arguing that it accesses emotion to alter the consciousness of percipients. Audiences respond with unusual intensity to Uranium's tragic environmental narrative. By using puppet theatre, film, comedy, and song to win their trust, Wiseman is able to shock his spectators. With interviews and consideration of the semiotic content of Uranium, I explore possibilities for activation of ecological consciousness through performing arts. Building on the shared ideas of Heinrich von Kleist, Gregory Bateson, and Thomas Turino, I argue that Wiseman offers one particularly useful mechanism to advance environmental concerns and learning through the arts. This paper seeks to bridge environmental and (ethno)musicological thought, and has specific relevance to the growing field of ecomusicology, presenting a musical ethnographic case-study in singer-song-writer activism.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.005
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.066
GPT teacher head0.188
Teacher spread0.122 · 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
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

Citations2
Published2014
Admission routes1
Has abstractyes

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