A White, Jewish, Rap-Infused Desire for Blackness: David Burd's Lil Dicky
Bibliographic record
Abstract
Known by his moniker Lil' Dicky, David Burd has been making rap music with an exceedingly Jewish twist for several years. This paper examines the Jewish and racial implications, and especially the intersections between the two, in Burd's lyrics and videos. Using James Baldwin's commentary on the Jewish-American condition in "On Being 'White' and Other Lies" as a starting point, I consider how Burd utilizes Jewish identity markers as a stand-in for Blackness in order to give his rap a unique ethnic position. Through three of his songs, I analyze the ways that Burd's relationship with race has evolved, culminating in his 2018 single "Freaky Friday" where Lil' Dicky and Chris Brown 'switch bodies'. In this song Dicky is able to say the N-word by having been placed by Burd into a Black body. Burd's music reflects a piece of contemporary, White, Male, Jewish consciousness and has implications for those who see themselves reflected in it.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".