Theorizing the hypeman in Nigerian popular culture: poetics, performance, and the e-fraud economy
Bibliographic record
Abstract
This paper theoretically explores the transformation of traditional praise-singing into hyping in Nigerian popular culture. Based on the proliferation of these performances in clubs, youth gatherings and social media, we argue that the hypeman figure emerges from the intersection of traditional praise-singing, hustler masculinity, youth hustle, flagrant elitism, conspicuous consumerism, e-fraud economy and popular culture as a high-demand commodity normalizing wealth from unknown sources and laundering the image of youth hustlers, especially internet fraudsters, even as it cannibalizes the tropes of praise-singing. We trace the genesis of hyping through our theorization of flagrant elitism as a model that defines contemporary Nigerian social reality. We also present a close reading of some hypeman performances in terms of context, poetics and performance aesthetics to underscore how they instantiate the transformation of African cultural modernity into the logic of European-inflected modernity and the historico-economic changes that necessitated and produced hyping as a performance genre.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".