Bibliographic record
Abstract
Over the past five decades, hip hop has become a widely celebrated genre of music, yet misconceptions still exist surrounding the hip hop community’s norm of sampling. This paper explores the origins of hip hop and the concept of sampling that is central to the genre. Sampling can be conceptualized as an eight-pronged framework involving three types of wholesale appropriation, three types related to lyrical quotation, and two types related to the variety of music or beats. Each type is discussed, and some examples are given. Following this overview, the ethics of sampling is explored via the context of the origins of copyright in the United States, which, some consider, to be a sampling of the first copyright law from Great Britain, the Statute of Anne. Historic litigation against hip hop artists is also discussed, as well as how these specific cases changed the attitude of record labels and their willingness to allow their artists to sample from outside the genre. The paper culminates with a discussion on various sampling norms within various communities and how they can be viewed as potential ways to revitalize U. S. copyright law.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.031 | 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 teacher head, 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".