Blood, Soil and Zombies: Afrofuturist Collaboration and (Re-)Appropriation in Nalo Hopkinson’s Brown Girl in the Ring
Bibliographic record
Abstract
In her Afrofuturist novel, Brown Girl in the Ring , Nalo Hopkinson unravels the psychological, cultural and historical trauma of the zombie figure. More than simply a supernatural element of the text, the zombie, and more particularly the latent psycho-social trauma it fantastically embodies, forms the very bedrock of the Afrocentric setting in a way that exposes and critiques the continued suffering of African diasporic peoples under racialized economic structures. While the origins of the zombie document Haitian anxieties surrounding slave labor, the zombie’s contemporary form, in reflecting middle class preoccupations with global capitalist consumption, highlights the ways in which cultural appropriation of Afrocentric culture helps perpetuate a larger systemic cycle of violence that erases black pasts while collapsing black futures into an uncertain present. This paper will explore the ways in which Hopkinson uses her vision of a dystopian Toronto that entraps and vilifies its poor racialized citizens (for the protection of its larger population) to challenge neoliberal global dominance. Through her re-privileging of Afro-Caribbean spiritual systems and knowledge frameworks, Hopkinson suggests that only by challenging and seeking alternatives to the epistemologies inherited by European modernity can we hope to counteract the violence they continuously enact upon global populations and revive hope for the prosperity of black life in the future. However, while her novel implicates cultural appropriation as part of a larger, white supremacist institutional regime, her novel’s framing of Afrocentricity on diasporic Indigenous soil highlights further challenges of Afrocentric representation in Afrofuturist literature.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.026 | 0.025 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".