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Record W7071556501

Tough Vinyl: Packing In Our Record Collections

2018· other· en· W7071556501 on OpenAlexaffabout

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
Fundersnot available
KeywordsCommodityArgument (complex analysis)Quarter (Canadian coin)Event (particle physics)AnthropoceneAssemblage (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

This paper seeks to illuminate a series of contradictions between the way we talk about, write about, and interact with vinyl records on the one hand, and the material and social relations required for the use, production, and disposal of vinyl records on the other. I examine vinyl as both an ethical commodity (the sonic equivalent to slow food) and as "the poison plastic"; vinyl as both a medium for "subaltern" voices and as a toxic substance that causes cancer in the bodies of working class communities of colour; and vinyl as it both preserves the dead and destroys the living. These contradictions and many more, all part of what I call the vinyl-network, are exposed throughout this paper in a process of de-fetishizing vinyl. The central argument of this paper is that the nostalgia for petrocapitalism's 20th century bounty (of which records are an iconic piece), is a dangerous fetish that perpetuates destructive social and material relations. Ultimately, I contend we need to abandon the vinyl revival and mourn the vinyl record, lest the way we listen to recorded music perpetuate the destructive economic system that is petrocapitalism, enabling it to spin on and on like a broken record. If we cannot move beyond this economic system, the dead will continue to pile up; we will repeat the same tragedies, different not in cause but in effect, as temperature and sea levels rise, as the Anthropocene Extinction Event wipes out one quarter of all mammals on earth, and as the screams of the dying are drowned out by the bourgeoisie's hi-fi. This paper concludes with the suggestion that we take the broken record that is petrocapitalism, smash it into a million pieces, and feed it to a hungry colony of soil fungi.

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)0.005
metaresearch head score (Gemma)0.020
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: Other · Consensus signal: Other
Teacher disagreement score0.075
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0140.007
Scholarly communication0.0150.017
Open science0.0020.014
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0750.018

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 head0.013
GPT teacher head0.176
Teacher spread0.163 · 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
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
Published2018
Admission routes2
Has abstractyes

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