Activity Analysis and Coordination in Continuous Responses to Music
Bibliographic record
Abstract
Music affects us physically and emotionally. Determining when changes in these reactions tend to manifest themselves can help us understand how and why. Activity Analysis quantifies alignment of response events across listeners and listenings through continuous responses to musical works. Its coordination tests allow us to determine if there is enough inter-response coherence to merit linking their summary time series to the musical event structure and to identify moments of exceptional alignment in response events. In this paper, we apply Activity Analysis to continuous ratings from several music experiments, using this wealth of data to compare its performance with that of statistics used in previous studies. We compare the Coordination Scores and nonparametric measures of local activity coordination to other coherence measures, including those derived from correlations and Cronbach’s α. Activity Analysis reveals the variation in coordination of participants’ responses for different musical works, picks out moments of coordination in response to different interpretations of the same music, and demonstrates that responses along the two dimensions in continuous 2D rating tasks can be independent.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".