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Record W4390356701 · doi:10.1525/res.2023.4.4.325

Elephant in the Matrix

2023· article· en· W4390356701 on OpenAlexaboutno aff
Freya Zinovieff, Milena Droumeva, G Sepúlveda

Bibliographic record

VenueResonance The Journal of Sound and Culture · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPraxisScholarshipSociologyHegemonyEpistemologyColonialismSound (geography)Relation (database)DecolonialityInstitutionAestheticsPolitical scienceLawSocial sciencePoliticsComputer science

Abstract

fetched live from OpenAlex

With the maturing of sound studies, and its intersection with critical studies, more attention is being given to the Anglo-Euro-centric and hegemonic legacy of acoustic ecology, as well as the cultural dimensions of sound studies. Discord between the practice of sound inquiry and sound ethnography has thus ensued, signaling the need to reexamine language and concept limitations, long-standing methods, approaches, and assumptions embedded in sonic research. In this paper we question the colonial foundations of sound studies in relation to researcher positionality and the conflicted task of attempting decoloniality from within the colonial institution that is academia. Beginning with a vignette, we position ourselves at the intersections of the discourse of coloniality and empire, and ask how sound studies, and indeed our own scholarship, mobilizes structures of power. Then we review major strands of decolonial scholarship within Canada and from key Latin American theorists, in relation to Canadian sound studies. And lastly, we offer what we call a speculative sonic framework for decolonial praxis: a set of suggestions for researchers that starts with the experiential more broadly, and the sonic more specifically, to mobilize decolonial praxis at the core of the research design.

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 score0.625
Threshold uncertainty score0.219

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.262
Teacher spread0.190 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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