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Record W2026316212 · doi:10.1386/jmte.2.2-3.97_1

Exploring a virtual music community of practice: Informal music learning on the Internet

2009· article· en· W2026316212 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

VenueJournal of Music Technology and Education · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCyberspaceInformal learningCommunity of practiceMusic educationOnline communityLearning communityEthnographyPedagogyThe InternetSociologyNarrativeLifelong learningIrishInformal educationPsychologyComputer scienceWorld Wide WebHigher educationArtPolitical science

Abstract

fetched live from OpenAlex

Over the past ten years, online communities of practice have evolved in cyberspace formed around different folk music genres, including Bluegrass, Irish Traditional, and Old Time (OT) music. Using Wenger's (1998) social learning theory as a framework, and informed by Hine's research in cyber ethnography (2000), the purpose of this article is to explore the informal music teaching and learning practices that characterize the OT music online community as a community of practice (CoP). What defines the OT online community as a CoP? What technologies including software programs do learners use and how do learners modify these to fit their needs? What practices characterize learning in this online community? Information gleaned from this article will serve a twofold purpose. First, the exploration of music learning in this online CoP will have implications for lifelong music learning and formal school music education. Second, this study will demonstrate the appropriateness of employing cyber ethnography as a method for conducting online narrative research in music education.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.124
GPT teacher head0.272
Teacher spread0.149 · 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