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Record W1560244212

Acoustic ecology and the cinematic representation of architectural space: Strains of R. Murray schafer's acoustic design in the films of Jacques Tati

2007· article· en· W1560244212 on OpenAlexaffvenue
Randolph Jordan

Bibliographic record

VenueCanadian acoustics · 2007
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsRepresentation (politics)Space (punctuation)Sound (geography)EcologyUrban sprawlVisual artsArtSociologyAcousticsAestheticsArt historyLinguisticsPhysicsUrban planningPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Acoustic ecology and the cinematic representation of architectural space is discussed with a particular focus on the strains of R. Murray Schafer's acoustic design in the films of Jacques Tati. R. Murray Schafer aims to develop awareness about the way modern spaces create and shape sound, and move towards the design of such spaces with an appreciation for how their sound affects their inhabitants. French filmmaker Jacques Tati made a career out of fashioning cinematic explorations of the sonic differences between old-world community spaces, urban environments, and the increasing sprawl to suburbia in the 50s and 60s. Film sound in terms of Acoustic Ecology in general, and the work of R. Murray Schafer in particular, can offer a new paradigm in which formal and aesthetic analysis can be carried out within the discipline of Film Studies. The study of the cinematic representation of space can offer new paths for exploration within the field of Acoustic Ecology.

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)0.005
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 score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.013
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.356
Teacher spread0.318 · 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

Citations0
Published2007
Admission routes2
Has abstractyes

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