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Sonic Sovereignty

2023· book· de· W4384833272 on OpenAlexaboutno aff
Liz Przybylski

Bibliographic record

VenueNew York University Press eBooks · 2023
Typebook
Languagede
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSovereigntyPolitical scienceLaw

Abstract

fetched live from OpenAlex

What does sovereignty sound like? Sonic Sovereignty considers how contemporary Indigenous musicians champion self-determination through musical expression in Canada and the United States. The framework of “sonic sovereignty” connects self-definition, collective determination, and Indigenous land rematriation to the immediate and long-lasting effects of expressive culture. Liz Przybylski covers online and offline media spaces, following musicians and producers as they, and their music, circulate across broadcast and online networks. Przybylski documents and reflects on shifts in both the music industry and political landscape over the course of a decade: as the ways in which people listen to, consume, and interact with popular music have radically changed, extensive public conversations have flourished around contemporary Indigenous culture, settler responsibility, Indigenous leadership, and decolonial futures. Sonic Sovereignty encourages us to experiment with temporal possibilities of listening by detailing moments when a sample, lyric, or musical reference moves a listener out of normative time. Nonlinear storytelling practices from hip hop music and other North American Indigenous sonic practices inform these generative listenings. The musical readings presented in this book thus explore how musicians use tools to help listeners embrace rupture, and how out-of-time listening creates decolonial possibilities.

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), Science and technology studies, 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: Other
Teacher disagreement score0.586
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.154
GPT teacher head0.210
Teacher spread0.056 · 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
Published2023
Admission routes1
Has abstractyes

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