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Record W1596130250 · doi:10.21083/csieci.v8i1.1965

Improvocracy, or Improvising the Civil Rights Movement in Wadada Leo Smith’s Ten Freedom Summers

2012· article· en· W1596130250 on OpenAlexaffvenue
Daniel Fischlin

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2012
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsImprovisationNarrativeVisual artsMusicalMovement (music)JazzPerformance artLyricsHistoryParadeArtBallroomLiteratureLawArt historyPolitical scienceAesthetics

Abstract

fetched live from OpenAlex

Improvising trumpeter and composer Wadada Leo Smith has consistently attended to the linkages between musical improvisation and social justice issues in his work over a long and remarkably productive career marked by a prodigious output of independently-minded music. Having recently celebrated his seventieth birthday by performing with six groups over two nights at Roulette in New York, he has also just released a milestone achievement—Ten Freedom Summers (Cuneiform Records, 2012)—dedicated to exploring through improvised and composed musicking the resonances of the American Civil Rights Movement from 1954 to 1964. This four-CD set of nineteen pieces, totaling some four and half hours of music, is also a three-night performance event that uses videography (but no spoken word interjections) organized around three sections that oscillate between composition and improvisation. Smith’s searing, incendiary, clarion-clear trumpet provides a narrative line that sustains throughout.

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)0.004
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: none
Teacher disagreement score0.020
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.023
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.058
GPT teacher head0.360
Teacher spread0.302 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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