Investigating soundscape affordances through activity appropriateness
Bibliographic record
Abstract
Central to the concept of soundscape is the understanding of the acoustic environment in context. Previous research indicates that people understand soundscapes through their potential for activities. One way to look at activities is through the concept of affordances - defined as the actionable properties of an object. In this study, the object is a location and time in the city. Fifteen participants listened to stereo recordings of 8 outdoor sites in Paris and Montreal. In each trial, they evaluated on a continuous scale how appropriate the soundscapes were for a given activity. Four activities were considered and presented in random order: studying for an exam, meeting up with a friend, riding a bike and relaxing. Participants justified their ratings in free-format comments. A 8(Soundscapes) x 4(Activities) factorial ANOVAs revealed significant effects of Soundscape and Activities and Soundscape*Activities on appropriateness ratings. Certain soundscapes were found to accommodate specific activities only while others were found to potentially accommodate all activities or none (prominent mechanical/traffic noise.) We also analyzed comments to further understand how participants envision utilizing the soundscape/environment and attribute meanings to the various sounds present.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".