MétaCan
Menu
Back to cohort
Record W2795768019 · doi:10.1145/3173574.3173678

On the Design of OLO Radio

2018· article· en· W2795768019 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMetadataActive listeningCuriosityComputer scienceWorld Wide WebContemplationResource (disambiguation)Space (punctuation)Interaction designMultimediaHuman–computer interactionPsychologyCommunication

Abstract

fetched live from OpenAlex

With the massive adoption of music streaming services globally, metadata is being generated that captures people's music listening histories in more precise detail than ever before. These metadata archives offer a valuable and overlooked resource for designing new ways of supporting people in experiencing the music they have listened to over the course of their lives. Yet, little research has demonstrated how metadata can be applied as a material in design practice. We describe the design of OLO Radio, a device that leverages music listening history metadata to support experiences of exploring and living with music from one's past. We unpack and reflect on design choices that made use of the exacting precision captured in listening history metadata archives to support relatively imprecise qualities of feedback and interaction to encourage rich, open-ended experiences of contemplation, curiosity, and enjoyment over time. We conclude with implications for HCI research and practice in this space.

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.

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: none
Teacher disagreement score0.940
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

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

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 head0.047
GPT teacher head0.279
Teacher spread0.232 · 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

Quick stats

Citations63
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicInnovative Human-Technology InteractionFrench-language works237,207