The Grapevine Telegraph "Jes Grew": Sonic Materialism, Afrofuturism and Information Theory in Ishmael Reed's Mumbo Jumbo
Bibliographic record
Abstract
Ishmael Reed's Mumbo Jumbo situates the history of African American culture in the language of genetics, information theory, biocultural evolutionism and sonic/vibrant materialism. Reed's motif of “Jes Grew,” as an evolving acoustic entity vibrant through radio technology, signifies a codified medium of information storage and transfer; it stores and transfers black cultural information in a viral form, articulating it to the physicality and orality of the antebellum grapevine telegraph. Such a biosonic construction of African American experience provides fertile terrain to explore the marginalization and rehabilitation of black ontological forces. By dramatizing the production and transmission of black tonality, Reed's trope of “Jes Grew” signals vibrational forces that counteract Western, white cultural norms. Thus Mumbo Jumbo's trope of the Jes Grew virus participates in, and advances, the aesthetic politics of Afrofuturism, in which Jes Grew's bio-sonic effects enable us to contest the narrow humanism of Eurocentric biopolitics with an Afrofuturist sonic materialism. By the same token, the novel's description of 1920s Harlem revolves around an epistemological framework of modern technoculture in which biological research becomes a textualization of nature and DNA becomes an information storage and transfer system. Mumbo Jumbo perceives the biological human body as an outcome of dynamic interactions in which information networks and social, cultural and biological relations are scripted in textual and coded platforms of sonic materialism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".