Bibliographic record
Abstract
This article engages the narratives of three Toronto hip-hop artists to explore the pedagogical possibilities revealed through the processes of performance identity construction. By immersing themselves in hip-hop communities, artists learn ways of knowing and negotiating their place at the interstices of the normative frameworks that underlie their unique combinations of cultural contexts. Artists’ stories reveal how they bring themselves into being through movement and sound. These narrations of identity become indicative of an artist’s style through performative iterations embedded with the opportunity for enacting difference. For hip-hop artists, deviating from performative expectations is not a mere possibility, but formative intention in the tradition of the African American practice of Signifyin(g), as delineated by Henry Louis Gates, Jr. Conversations with hip-hop artists invite reflection on what we could accomplish through a music education pedagogy that cultivates creative deviancy that reveals, breaks open and overturns limiting conventions.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".