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Record W3160823153 · doi:10.1386/ajpc_00025_1

Vapor Memory, or, memory in the ruins of history

2020· article· en· W3160823153 on OpenAlexaff
David Guignion

Bibliographic record

VenueAustralasian Journal of Popular Culture · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsWestern University
Fundersnot available
KeywordsCapitalismAestheticsAppropriationIdeologyOppressionHumanismArgument (complex analysis)SociologyLate capitalismPoliticsEpistemologyPhilosophyLawPolitical science

Abstract

fetched live from OpenAlex

This article explores vaporwave’s appropriation of the past and future to constitute a (non)-site for the displacement of the present. In doing so, vaporwave – an electronic music genre that samples sights and sounds from 1980s and 1990s popular culture – masquerades itself as a radical project that decentres the subject’s location within the linear matrix of time () and houses the potential to oppose the humanistic territorializations of late capitalism (; ). I argue that these arguments focus too closely on vaporwave’s style and aesthetic dimension without considering its maintenance of various structures of oppression and appropriation indicative of globalized capitalism. The result is a misattribution of transgressive potential to vaporwave that ignores its incredibly conservative undertones. To engage with vaporwave then demands a bifurcation of its outward, rhizomatic veneer and the codes, conventions and axiomatics that underwrite it. I make this argument by drawing upon Jean , , , ) scepticism of any accelerationist and technologist politics of subversion to mount effective sociopolitical change. Additionally, I make use of many feminist and critical race approaches to highlight the affinities between vaporwave’s appropriate style and the logics of late capitalism.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.995

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.238
Teacher spread0.171 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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