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Record W4409721592 · doi:10.1145/3706599.3721353

Exploring distributed co-listening experiences through tempo-based interactions with Queue Player

2025· article· en· W4409721592 on OpenAlexafffund
Samuel Barnett, Samann Pinder, William Odom

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsActive listeningComputer scienceQueueDistributed computingComputer networkPsychologyCommunication

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.157
GPT teacher head0.405
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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