YouTube, fanvids, forums, vlogs and blogs: Informal music learning in a convergent on- and offline music community
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.
Bibliographic record
Abstract
In this paper I examine the music learning and teaching in the Banjo Hangout online music community ( www.banjohangout.org/ ) using cyber ethnographic methods of interview and participant observation conducted entirely through computer-mediated communication, which includes Skype and written narrative texts – forum posts, email, chat room conversations – along with hyperlinks to YouTube and other Internet music-learning resources. The Hangout is an example of an online community based on the pre-existing offline interests of its founding members and it is thus connected to and overlaps with the offline Old Time and Bluegrass music banjo communities. Although I focus on the Banjo Hangout online community, this study also provides peripheral glimpses – embedded in the participants’ narratives – into the offline Old Time and Bluegrass banjo communities of practice. As a cyber ethnographic field study, this research also highlights the epistemological differences between on- and offline community as reflected in music education online narrative qualitative research and research practice.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it