Rethinking the Underclass: Future Directions in Southern African Labor History
Bibliographic record
Abstract
Southern and South African labor history has, at least since the 1970s, been as much about the future of the region as about its past. Liberal scholars saw in apartheid and segregation irrational aberrations to the color-blind logic of capitalism. They believed the apartheid state to be an instrument of racial dominance but saw it as more or less neutral in terms of class relations. Economic growth and the abolishment of racial laws would bring freedom and equality—or at least equal opportunities. On the other hand, radical historians and sociologists thought of apartheid as a system that guaranteed the exploitation of cheap black labor for the benefit of capital. For them, apartheid was functional to capitalism.2While both the liberal and the radical positions were often more nuanced than the other side would admit, the question that divided these two camps was one about politics and strategy: Would capitalist development bring an end to racial domination, or was it part of the problem? In the latter case, challenging apartheid and colonialism would also involve challenging capitalism. The vibrancy of these debates should continue to serve as an inspiration for labor historians. I will argue that for the Left to be able to formulate viable alternatives to present policies, we should look at the history and nature of labor and inequality in the region.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".