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Record W4407281879 · doi:10.1016/j.exis.2025.101624

Mining global decarbonisation for development in Africa? Regional geopolitics and the question of South Africa in Africa

2025· article· en· W4407281879 on OpenAlexafffund
Michael Smith

Bibliographic record

VenueThe Extractive Industries and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsYork University
FundersDepartment of Higher Education and TrainingYork University
KeywordsGeopoliticsPolitical scienceDevelopment economicsGeographyInternational relationsEconomic growthEconomic geographyEconomyPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.319
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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