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Record W2004044116 · doi:10.1121/1.2935516

Soundscapes: from noise annoyance to the music of urban life

2008· article· en· W2004044116 on OpenAlexaff
Catherine Guastavino, Danièle Dubois

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsSoundscapeDiversity (politics)PerceptionInterpretation (philosophy)Noise (video)Meaning (existential)Natural (archaeology)SociologyCognitive psychologyComputer sciencePsychologyEpistemologyAcousticsHistoryArtificial intelligenceAnthropologySound (geography)Philosophy

Abstract

fetched live from OpenAlex

Through an overview of empirical research over the past ten years, we present an interpretation of the evolution of the concept of soundscape. From a strictly acoustic definition in terms of physical descriptors, it evolved into a more complex notion integrating the effects of noise on citizens. Soundscape research therefore requires the contribution of human sciences (psychology of perception, cognitive psychology, sociology, anthropology of senses). There is converging evidence that people judgments of noise is related to the meaning given to the activities producing the noise. Consequently, physical descriptions in acoustics have to face the diversity of human reactions to noise correlated with the diversity of activities, the diversity of source producing noises within a diversity of physical environments (natural, architectural). This paper focuses on major emerging issues in soundscapes research, namely - the integration of such a diversity of pieces of knowledge within a general knowledge - the translation of these diverse conceptualizations into physical descriptions - the elaboration of convincing physical measurements for decision makers. We will draw consequences for further developments in the cooperative and pluridisciplinary research and for producing guidelines for new orientations in community policies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.318
Teacher spread0.285 · 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 teacher head, 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

Citations2
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicNoise Effects and ManagementFrench-language works237,207