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Record W2117949706 · doi:10.21083/csieci.v7i2.1675

“A Door to Other Doors”: Henry Threadgill Interview with Daniel Fischlin

2011· article· en· W2117949706 on OpenAlexaffvenueabout
Daniel Fischlin

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMusicalJazzConcertoPerformance artVisual artsViolinArtArt historyDismissalAppealClassical musicMOZARTGuitarDanceSociologyLawPianoManagementPolitical science

Abstract

fetched live from OpenAlex

Henry Threadgill is one of the great original, iconoclastic voices in American music, and sits comfortably with other great voices from the U.S. and elsewhere: from Charles Ives through to Aaron Copland and Elliot Carter; from Ornette Coleman and Albert Ayler through to Anthony Braxton and John Zorn; from Igor Stravinsky through to Edgard Varèse and Luciano Berio. In this extended interview with Daniel Fischlin, Threadgill covers aspects of his personal history as a youth growing up in Chicago, his first contact with the AACM and other experimentalist musicians in Chicago, his thoughts on the connections between improvised music and the Civil Rights Movement, and a lengthy reflection on the importance of improvised music and its pedagogy. Conducted in public before a large audience of 2011 Guelph Jazz Festival goers, the interview shows Threadgill as an eloquent, impassioned, and astute observer of musical phenomena, especially in his appeal to improve access to quality musical education in North America and in his dismissal of the attempt to impose European musical structures on African American forms of musicking based on “replication” as opposed to “creation.”

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)0.003
metaresearch head score (Gemma)0.009
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 score0.132
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0250.011
Scholarly communication0.0070.008
Open science0.0010.003
Research integrity0.0070.009
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 head0.182
GPT teacher head0.342
Teacher spread0.161 · 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

Citations0
Published2011
Admission routes3
Has abstractyes

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