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Record W1973770488 · doi:10.1017/s1355771809000120

<i>The Icebreaker</i>: Soundscape works as everyday sound art

2009· article· en· W1973770488 on OpenAlexaff
Owen Chapman

Bibliographic record

VenueOrganised Sound · 2009
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsSoundscapeSound (geography)Sound artNoticeMusicalVariety (cybernetics)AcousticsJohn CageFocus (optics)Visual artsComputer scienceAestheticsArtPerformance artLaw

Abstract

fetched live from OpenAlex

The following discusses the potential of soundscape work to reveal new aspects of our everyday aural environments. Openness to the voice(s) of one’s sonic surroundings is maintained as a hallmark of soundscape works, and also a key component of sound art more generally. Different perspectives and questions are articulated, with a consistent focus on the variety of spaces engaged by both sound(scape) artists and listeners. A case study is presented – a recently initiated sound art project on the part of the author entitled The Icebreaker. The latter is a musical instrument, performance piece and interactive installation made from piezo microphones and ice. Prepared compositions, including soundscape works, are diffused at different moments when one ‘plays’ The Icebreaker. I describe this emergent work as an example of the sort of considerations and negotiations that are at the heart of soundscape/sound art composition. My aim is to demonstrate how sound artworks bring us to attend to sounds we formerly failed to notice, revealing our own reactions to these stimuli at the same time.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.016
Scholarly communication0.0130.006
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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
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

Citations6
Published2009
Admission routes1
Has abstractyes

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