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Record W2617617917 · doi:10.7202/1039658ar

Curating Ethnomusicology in Cyberworlds for Ethnomusicological Research

2017· article· en· W2617617917 on OpenAlexaffvenue
Michael Frishkopf, Michael Cohen, Rasika Ranaweera

Bibliographic record

VenueEthnologies · 2017
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEthnomusicologyMusicalExhibitionVisual artsAestheticsSociologyArt

Abstract

fetched live from OpenAlex

We describe a musical cyberworld as a virtual space for curating ethnomusicology, as well as for conducting research: the ethnomusicology of controlled musical cyberspaces. Our cyberworld differs from most online music curation in enabling immersive, social experience. Considering such cyber-exhibition of ethnomusicological research as itself a form of social and musical practice also calls for an ethnomusicology of such exhibits. Research in ethnomusicology has typically been conducted through qualitative fieldwork in uncontrolled settings. By contrast, we design a custom musical cyberworld as a virtual ethnomusicological laboratory, a platform for research geared towards better ways of designing online musical exhibitions for discovery, learning, and aesthetic contemplation, as well as contributing towards our general understanding of the role of music in human interaction and community formation.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0040.003
Research integrity0.0010.001
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 head0.237
GPT teacher head0.441
Teacher spread0.204 · 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.

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

Citations1
Published2017
Admission routes2
Has abstractyes

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