Bibliographic record
Abstract
This paper engages with the epistemological assumptions of diaspora as it has been narrativised within North American discourses of Black identity formation. It will be argued that in light of the rapid growth of Black African migrant women populations in both the United States and Canada, and their second generation descendants over the past four decades, new frameworks for understanding Blackness are needed. The experiences of Black identity formation among these women in North America are particularly susceptible to exclusion within older and more dominant frameworks for narrativising histories of slavery, migration and Blackness. I will argue that Black feminist speculative fiction, with its history of subversion and reputation for unbound imagination, can be useful in addressing this exclusion. Thus, using Octavia Butler’s 1980 novel Wild seed as a case study, I will argue throughout this paper that Black feminist speculative fiction presents epistemological tools useful in exploring the limits of these older frameworks, while still drawing from them in order to create newer and/or more flexible epistemologies better suited to the gendered, ethnic and sexual differences within Black diasporic communities, especially those that have come about as a result of these newer migrations from Africa.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".