What does capital consume? Racial capitalism and the social reproduction of surplus people
Bibliographic record
Abstract
This intervention considers uneven development and social reproduction within racial capitalism. Social reproduction refers to the range of practices that form the conditions of possibility for the life of capital, as well as life and death within racial capitalism. This spans a range of institutions and networks within households, communities, states and across national borders as well as the labour practices, relations and organization that reproduce racial capitalism. Here, we examine the extraction of time, taking up theorizations across carceral geographies, postcolonial theory and Caribbean studies to demonstrate how coercive relations of social reproduction contribute to uneven development. In particular, we look at the role of the state in racial capital’s capture of reproductive activities across our work on electric utilities in Atlanta, Georgia and extralegal land tenure on Jamaica’s north coast. In bringing these distinct sites into conversation, we re-affirm the need to study uneven development by understanding how the circulation and accumulation of capital is imbricated with the production of hierarchies of all kinds of difference. We show how a conjunctural countertopography can reveal how state practices advance accumulation under conditions of widespread surplus lives, as capital wagers on captive life and premature death.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 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".