Black (W)hole Foods: Okra, Soil and Blackness in The Underground Railroad (Barry Jenkins, USA, 2021)
Bibliographic record
Abstract
This essay analyses the role played by okra in The Underground Railroad, together with how it functions in relation to the soil that sustains it and which allows it to grow. I argue that okra represents an otherwise lost African past for both protagonist Cora and for the show in general and that this transplanted plant, similar to the transplanted Africans who endured the Middle Passage on the way to ‘New World’ slave plantations, survives by going through ‘black holes’, something that is not only linked poetically to the established trope of the otherwise absent Black mother but which also finds support from physics, where wormholes (similar to the holes created by worms in the soil) take us through black holes and into new worlds, realities or dimensions. This is reflected in Jenkins’s series (as well as Whitehead’s novel) by the titular Underground Railroad itself, which sees Cora and others disappear underground only to reappear in new states (the show travels from Georgia to South Carolina to North Carolina to Tennessee to Indiana and so on), as well as specifically in the show through the formal properties of the audio-visual (cinematic/televisual) medium, which, with its cuts and movements, similarly keeps shifting through space and time in a nonlinear but generative fashion. Finally, I suggest that we cannot philosophise the plant or the medium of film (or television or streaming media) without philosophising race, with The Underground Railroad serving as a means for bringing together plants and plantations, soil and wormholes and Blackness and black holes, which, collectively and playfully, I group under the umbrella term ‘black (w)hole foods’.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".