Black living standards in South Africa before democracy: New evidence from height
Bibliographic record
Abstract
Very little income or wage data were systematically recorded about the living standards of South Africa’s black majority during much of the 20th century. We used four data sets to provide an alternative measure of living standards – namely stature – to document, for the first time, living standards of black South Africans over the course of the 20th century. We found evidence to suggest that living standards in the first three decades of the century were particularly poor, perhaps because of the increasingly repressive labour policies in urban areas and famine and land expropriation that weighed especially heavily on the Basotho. The decade following South Africa’s departure from the gold standard, a higher international gold price and the demand for manufactured goods from South Africa as a consequence of World War II seem to have benefitted both black and white South Africans. The data also allowed us to disaggregate by ethnicity within the black population group, revealing levels of inequality within race groups that have been neglected in the literature. Finally, we compared black and white living standards, and revealed the large and widening levels of inequality that characterised 20th-century South Africa. Significance: We provide the first long-run estimates of black living standards in South Africa and evidence of inter-group differences in the effects of 20th-century events and policies.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".