Bibliographic record
Abstract
This paper explores the intertextual relationships between popular music songs and their jazz adaptations, or “covers.” In a jazz adaptation of a pop song, the improvisatory sectionwedged between two more or less complete statements of the pop songforms the crux of the jazz performance. Improvisation affords musicians an opportunity to create something new out of an existing musical work and, as I suggest in this paper, has the potential to transform the expression perceived in the popular song’s lyrics and musical structure. Using Brad Mehldau’s live solo piano performance of Radiohead’s “Paranoid Android” (1997) from his promotional albumDeregulating Jazz([1999] 2000) as a case in point, I show how his adaptation both highlights the motivic repetitions in the original rock song and heightens the song’s expressions of anxiety and apprehension. The article unfolds in two sections. The first section provides an overview of Radiohead’s “Paranoid Android” as a means to ground my discussion of Mehldau's recording. Here I consider how the rock song’s musical content can be heard as the analog of its lyrical content. In the second section, I explore the intertextual relationships that emerge between Mehldau's adaptation and Radiohead's rock song, drawing from my transcriptions and analyses of both musical texts.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".