Muestreo de imagen de sonido en Fear of a Black Planet
Bibliographic record
Abstract
En este artículo, discutimos el patrón de muestreo utilizado en el álbum Fear of a Black Planet, lanzado en 1990, por el grupo de rap norteamericano Public Enemy. Como hipótesis, asumimos la idea de que el uso de muestras establece otra discursividad, paralela y articulada a los discursos y contenidos expresados en las letras de las composiciones. El uso de determinadas muestras, en cierto modo, crea un curioso “territorio de resignificación”, que trataremos de describir y problematizar. Por ello, en un principio nos dedicamos a la definición de la técnica del sampleo así como al reconocimiento de su importancia dentro de la cultura del rap y el hip hop. Luego, recurrimos a aportes teóricos muy concretos, que nos brindan, entre otros, Walter Benjamin (la noción de “cultura de choque”, por ejemplo), Vilém Flusser y el crítico literario español Eloy Fernández Porta (en este caso, la idea de “caída de nombres”). Concluimos con la ocurrencia de una arqueología muy particular de textualidades y discursos afirmativos.
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 | 0.009 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".