Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".