Bridging Critical Race Theory and Lockean Social Contract Theory: Derrick Bell’s “The Space Traders” as Proto-Racial Contract Theory
Bibliographic record
Abstract
The paper below was written for a course that focused on nonrealist literary works by authors of the African diaspora, framed within a larger diasporic tradition known as Afrofuturism. Afrofuturism, as Lisa Yaszek explains, is a “term . . . generally credited to [Mark] Dery,” who defines it as “’speculative fiction that treats African-American themes and addresses AfricanAmerican concerns in the context of 20th century technoculture — and more generally, African-American signification that appropriates images of technology and a prosthetically enhanced future’ to explore how people of color negotiate life in a technology intensive world” (Yaszek, “Afrofuturism, Science Fiction, and the History of the Future”). As Erik Nolan points out in his work below, however, Afrofuturist work can also deploy science fiction tropes to analyse social and political structures beyond the “technology intensive world.” As Nolan argues, Derrick Bell uses the standard science fiction trope of alien abduction specifically to explore the problems of the legal system in the US: a system that purports to be unbiased but is, in practice and theory, built on the exclusion and exploitation of Black people. — Dr. Jason Haslam
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.056 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| 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".