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Record W3199073185 · doi:10.1525/res.2021.2.3.377

Soundscapes of Productivity

2021· article· en· W3199073185 on OpenAlexaboutno aff
Milena Droumeva

Bibliographic record

VenueResonance The Journal of Sound and Culture · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsSoundscapeProductivitySociologyVisual artsSound (geography)ArtEconomic growthAcoustics

Abstract

fetched live from OpenAlex

Using the urban portmanteau terms “coffice” and “coffitivity” as a starting point, this paper examines ideas around sound and productivity with a focus on coffee shop ambiences. The project considers café soundscapes “soundscapes of productivity” reflective of changing attention spans, work process, and stress management that invoke cultural histories of Muzak, personalized sonic spaces, and the sonic management of everyday life. A result of over six years of ethnographic observations, recordings, and decibel measurements, Soundscapes of Productivity has also been compiled into a Story Map as a kind of soundwork collage of different coffee shop ambiences in Vancouver, Canada. Vancouver is used here for its local specificity, including a rapidly gentrifying urban infrastructure and a creative freelance haven with aspirations to be the Canadian Silicon Valley. The project presents an opportunity to link scientific discourses of the stimulus response model of sonic productivity historically and politically with the modern practice of productivity playlists, and bridge them together with acoustic environments seemingly replicating former factory production—environments such as the urban coffee shop.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.211
Teacher spread0.191 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

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