MétaCan
Menu
Back to cohort
Record W4281845906 · doi:10.12745/et.25.1.4484

Acousmatic Noise: Racialization and Resistance in The Tempest's 'New World' Soundscape

2022· article· en· W4281845906 on OpenAlexvenueno aff
Mayra Cortes

Bibliographic record

VenueEarly Theatre · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTempestRacializationResistance (ecology)ArtLiteratureHistorySociologyGender studiesRace (biology)

Abstract

fetched live from OpenAlex

I analyze Shakespeare’s racialization of noise in The Tempest as an acousmatic phenomenon and suggest how the acousmatic — sound whose source remains hidden — is imagined as a weapon of resistance that the racialized noisome Other could use to resist aristocratic and colonial power. Shakespeare’s play echoes the Algonquian-speaking Powhatan use of acousmatic singing in Tsenacommacah as a mode of warfare against the English in Virginia in 1611 with that of Caliban and his companions’ (Stephano and Trinculo) singing revolt.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

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 studies0.0100.018
Scholarly communication0.0070.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEarly TheatreSame topicHistorical Art and Culture StudiesFrench-language works237,207