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Record W2127780100 · doi:10.22230/cjc.2008v33n3a2000

Sonic Signage: [murmur], the Refrain, and Territoriality

2008· article· en· W2127780100 on OpenAlexaffvenue
Darren Wershler

Bibliographic record

VenueCanadian Journal of Communication · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSignagePhonographArgument (complex analysis)TerritorialitySound (geography)Code (set theory)HistoryPictogramMedia studiesVisual artsSociologySet (abstract data type)ArtEngineeringCommunicationComputer scienceAcousticsArchaeology

Abstract

fetched live from OpenAlex

[murmur] is an archival audio project that collects and curates stories set in cities around the globe. At each location, a distinctive [murmur] sign with a telephone number and location code marks where stories are available. While [murmur]’s signs evoke the tradition of neo-Situationist and neo-Lettrist signage, it is the sonic supplement to these signs that is of particular interest. This article contextualizes the relationships that [murmur] establishes between physical signage, recorded sound, and specific geographic locales in both historical and theoretical terms. Thomas Edison originally only permitted demonstrations of the phonograph according to a strict system of territorial licensing, suggesting that there has always been a link between visible language, recorded audio, and territoriality. The article’s argument contextualizes and expands on this historical relationship via Deleuze and Guattari’s essay “1837: Of the Refrain.”

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.031
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.134
GPT teacher head0.220
Teacher spread0.086 · 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 designQualitative
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

Citations5
Published2008
Admission routes2
Has abstractyes

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