Situational and person-related factors influencing momentary and retrospective soundscape evaluations in day-to-day life
Why this work is in the frame
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Bibliographic record
Abstract
Soundscape research draws on both experiments conducted in laboratory settings and studies in the field to explore peoples' perception and understanding of their acoustic environments. One opportunity to combine the strength of both approaches is the so-called Experience Sampling Method (ESM). This method was used to investigate the influence of situational and person-related variables on soundscape evaluations. Further, the relationship between momentary and retrospective soundscape judgments was explored. In the course of the 7-day ESM study, 32 participants were prompted ten times per day by a smartphone application to evaluate their soundscape and report on situational factors. Additionally, they performed summary retrospective judgments evaluating the whole of each day and their whole week. Upon completion, an exit interview probed personality traits (e.g., Big Five, information processing styles). Results revealed that both situational and person-related factors significantly contributed to the judgments of three soundscape dimensions (pleasantness, eventfulness, familiarity). Retrospective judgments of soundscape pleasantness were not only the average of the momentary judgments, but were also affected by the peak moment, the linear trend of the experience, and a person's mood while performing the judgment. Hence, the study provides valuable insights into the complex structure of momentary and retrospective soundscape evaluations.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it