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Record W2325194963 · doi:10.7202/017594ar

Acoustic Space1

2008· article· en· W2325194963 on OpenAlexvenueno aff
R. Murray Schafer

Bibliographic record

VenueCircuit Musiques contemporaines · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
FundersDepartment of Electronics and Information Technology, Ministry of Communications and Information Technology
KeywordsSoundscapeSound (geography)Space (punctuation)Set (abstract data type)AcousticsSociologyAestheticsVisual artsArtComputer scienceLinguisticsPhilosophyPhysics

Abstract

fetched live from OpenAlex

Starting from McLuhan’s concept of acoustic space, the author discusses how the World Soundscape which he undertook at Simon Fraser University in 1970 set out to put this notion into practice by studying how the soundscape influences all aspects of people’s lives. In the extract published here, the author finds that the sphere is the geometric shape which best describes acoustic space, and discusses the sybolism of the sphere – and of sound – in the cultures of the world.

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: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.006

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 head0.220
GPT teacher head0.235
Teacher spread0.015 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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