Bibliographic record
Abstract
Abstract Writing (“Aerosol Art”) is more than an inspiration for some Hip Hop dance practitioners. For those that combine the various elements in Hip Hop, the relationship between them is the generative impulse for creation. In the quest to create a personal signature in the city, Hip Hop arts express not only the visual name but also the rhythm of the letters, and how their movement connects to space and time. YNOT’s output as a B-boy is the result of investigations into other art forms and cultural backgrounds. The chapter identifies some of the practices of iconic artists that inspired YNOT’s output, such as RAMM:ELL:ZEE, Donald “DONDI” White, Jeffrey “DOZE” Green, and Jorge “POP MASTER” FABEL. It discusses how art schools are often places to gather and experiment and have contributed to creativity in Hip Hop culture. Understanding and relating the structures of art forms can deepen art practices and help decolonize disciplines. This chapter examines Hip Hop methodologies while showing how the integrity of this work is connected to knowledge of self and openness to divergent experiences.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".