Defining the Groove: From Remix to Research in <i>The Beat of Boyle Street</i>
Bibliographic record
Abstract
This paper represents musical remixing practices as a means of conducting leisure research. Our research engaged urban Aboriginal-Canadian youth through The Beat of Boyle Street, a music technology program used to teach young people how to produce their own remixes. Through this program we developed a “research remix” of narrative, Indigenous and arts-based ethnographic methods attuned to processes of making sense through making music. We examined the ways young people (re)produced not only songs but also stories, cultures and identities. Our research remix connects leisure practices and popular cultural processes by informing understandings of music and leisure in young people's lives. [Supplementary materials are available for this article. Go to the publisher's online edition of Leisure Sciences for the following free supplemental resources: sound clips of El Jefe remix (a capella), “Broken Home,” “Street Life,” and “Turning Point (a capella).”]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.055 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".