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Record W2161802767 · doi:10.1162/leon_a_00034

<i>Auditory Tactics:</i> A Sound Installation in Public Space Using Beamforming Technology

2010· article· en· W2161802767 on OpenAlexaffabout
Philippe-Aubert Gauthier, Philippe Pasquier

Bibliographic record

VenueLeonardo · 2010
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsSimon Fraser UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsSound (geography)BeamformingActive listeningSpace (punctuation)Computer scienceShadow (psychology)AcousticsNoveltyProjection (relational algebra)Public spaceHuman–computer interactionEngineeringSociologyPsychologyTelecommunicationsCommunicationArchitectural engineeringPhysics

Abstract

fetched live from OpenAlex

The term “auditory tactics” refers to the contextual listening attitudes and competencies adapted to various private and public auditory contexts, spheres and aural architectures. Auditory Tactics, created for the Pure-Data Convention 2007 in Montréal, is a spatial sound installation designed to interfere and play with the auditory tactics of passersby in a public space by projecting sounds from more private spheres. The novelty of the authors' work is the use of beamforming: a sound projection technology that allows the creation of directional sonic beams resulting in sonic illumination and shadow zones that dynamically interact with architectural surfaces. The authors report the results and lessons of this first artistic experiment with sound beams as a creative sound-projection method.

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: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.056
GPT teacher head0.347
Teacher spread0.291 · 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

Citations5
Published2010
Admission routes2
Has abstractyes

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