Exploring distributed co-listening experiences through tempo-based interactions with Queue Player
Bibliographic record
Abstract
As music streaming libraries continually grow, finding meaningful ways to revisit, reflect on, and share these collections over time—both individually and socially—becomes increasingly important. Queue Player is a network of four domestic music players that allow for synchronous distributed co-listening across geographical distance and for the long-term exploration of the collective music listening histories among four close friends. Queue Player leverages tempo metadata (i.e., beats per minute) as the cornerstone of its interaction design, enabling users to explore an ever-changing queue of songs from their collective pasts shaped by tempos steadily tapped out on their respective device. While the four Queue Players exist in real, highly finished physical form, this video offers an artistic explanation and user scenario of their outer and inner workings, drawing on stop motion, collage, and zine aesthetics to emphasize the reflective, temporal, material and subtly evolving conceptual qualities shaping the design of this system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".