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Record W4376058156 · doi:10.24908/lhps.v1i1.15561

“Sounds and sweet airs, that give delight, and hurt”

2022· article· en· W4376058156 on OpenAlexaff
Miranda Crowdus

Bibliographic record

VenueLiving Histories A Past Studies Journal · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsNarrativeAestheticsMetaphorPerformative utteranceMusicalIndigenousMelodyPopular musicMovie theaterHistoryLiteratureSociologyArtVisual artsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article addresses Indigenous film-maker, Lisa Jackson’s, skillful and strategic integration of selections of Western Art Music from the Early and Late Classical period in the soundtracks of her recent films. This strategy draws attention to indigenous perspectives on economic and cultural sustainability, as well as to the threat posed to indigenous continuity by colonialist legacies, past and present. In Jackson’s films, the excerpts from Western Art Music comprising the musical score “takes over” the narrative; their sound is pleasant, but unseen, insidious and triumphant, ultimately a duplicitous and malevolent dominating force. In my view, the selections from Western Art Music function as a metaphor for the unseen, insidious and ever-present forces of colonialism that control the negative behaviors and lives of the indigenous protagonists in the film narrative. This metaphor functions on both macro (formal and performative) and micro (melodic and chordal) levels. On a meta-narratival level, Jackson’s soundtracks draw attention to contemporary audience’s de-sensitization to the use of sonic repertoires in popular cinema and to the normalization of the congruence of sound and musical material and film narrative. Jackson’s adaptation of the musical material suggests that in order to shed colonialist legacies, we must also interrogate their often physical heard, but cognitively and critically unremarked, accompanying soundtracks.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score1.000

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 studies0.0070.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.234
Teacher spread0.128 · 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.

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
Published2022
Admission routes1
Has abstractyes

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