"The Cashtro Hop Project" Hip Hop music and an exploration of the construction of artistic self-identity
Bibliographic record
Abstract
While Hip Hop culture has regularly been legitimized within academia as a social phenomenon worthy of scholarly attention (witness the growing number of studies and disciplines now taking Hip Hop as object for analysis), this is the first Hip Hop-themed project being completed within the academy. Indeed, academic and critical considerations of one's own Hip Hop-based musical production is a novel venture; this project, as a fusion of theory with practice, has thus been undertaken so as to occupy that gap. The paper's specific concern is with how (independent) Hip Hop recording artists work to construct their own selves and identity (as formed primarily through lyrical content); the aim here is to explore Hip Hop music and the construction of artistic self· presentation. I therefore went about the task of creating my own album - my own Hip Hop themed musical product - in order to place myself in the unique position to examine it critically as cultural artifact, as well as to write commentary and (self-)analyses concerning various aspects of (my) identity formation. The ensuing outlined tripartite theoretical framework is to serve as a model through which other rappers/academics may think about, discuss, and analyze their own musical output, their own identities, their own selves.
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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 | 0.002 | 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 | 0.020 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".