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Record W2335391078 · doi:10.7202/1023108ar

Establishing Sound

2014· article· en· W2335391078 on OpenAlexvenueno aff
Rick Altman

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)HollywoodShot (pellet)Key (lock)Computer scienceAcousticsHistoryComputer securityArt historyPhysics

Abstract

fetched live from OpenAlex

The history of film sound has usually been configured as a series of technological upheavals. In every case, the story has been told through technological innovations, as if changes in technology were alone responsible for the development of new sound strategies. The approach offered here differs markedly from these previous treatments of sound. Instead of concentrating on technological shifts, this article stresses technical decisions made by the soundmen and directors responsible for developing Hollywood’s standard approach to sound. Through succinct analysis of two key films, The First Auto (Warner, 1927) and It Happened One Night (Columbia, 1934), along with briefer treatment of The Big Trail (Fox, 1930), a distinction is made between “shot-by-shot” treatment of sound and “scene-by-scene” treatment of sound. The systematic use of sound in It Happened One Night to establish and maintain a coherent sense of place gives rise to recognition of the increasingly common use of what the article terms “establishing sound.” Parallel to Hollywood’s familiar technique of introducing each scene with an “establishing shot,” the use of establishing sound offers filmmakers an additional method of locating auditors and maintaining their relationship to the film.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.228
Teacher spread0.190 · 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.

Study designTheoretical or conceptual
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

Citations4
Published2014
Admission routes1
Has abstractyes

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