Whose Pain Is It, Anyway?: On Kippie Moeketsi and John Chavafambira’s Encounter with Medical Science
Bibliographic record
Abstract
Black pain, while overwhelmingly real for those experiencing it, has an altogether incontestably singular structure that exposes the incompatibility of protocols of relief with the structure of anti-Blackness. Reading and reflecting on the late South African composer Kippie Moeketsi’s tragic sojourn in London’s Ferreira Hospital’s “mental asylum,” this paper probes, through an afropessimist critique, the tension between the unfettered access to and gratuitous enjoyment of the (pained) Black body and problem of Black thought. Instead of treating this incident as isolated, I trace it from Wulf Sachs’ psychoanalytic-cum-anthropological study of and relationship with a Black analysand, John Chavafambira, in his 1937 Black Hamlet (later adapted to Black Anger in a revised 1947 edition) to highlight a fundamental ambivalence and dependence of human social relations on Black pain for their coherence. Moreover, I interrogate the problem of the figure of the “mad African” and the supposed incongruity of their psychic structure with the demands of an anti-Black order.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.033 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| 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".