Mining global decarbonisation for development in Africa? Regional geopolitics and the question of South Africa in Africa
Bibliographic record
Abstract
Research into the geopolitics of ‘critical’ mineral mining is expanding. However, there remains a notable dearth of analysis concerned with addressing how global decarbonisation relates to regional relations and configurations of power. This absence is concerning given the relatively widespread acceptance that regional development strategies should be embraced by economies seeking to leverage their ‘green’ transition mineral endowment for industrialisation and development. This paper revisits the debate on character of the South African state in Africa, from the vantage point of the mineral intensity of global decarbonisation and the competitive dynamics of the contemporary global political economy. The paper primarily assesses the view that South Africa should be seen as a sub-imperialist actor in the maintenance of the global neoliberalism, arguing that this perspective offers a rigid view of the world capitalism and geopolitics and presents a thin theory of state formation and economic and social relations in the periphery. By examining South Africa's role in contemporary Zambia in the context of increasing international competition for access and control of Zambia's 'green' mineral reserves, the paper highlights the ambiguity of South African state action and the evolving and dynamic relations it forges with domestic and international class and state forces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| 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".