Temporality, Limited Statehood, and Africa’s Abandoned Mines
Bibliographic record
Abstract
Abstract Centering temporality when discussing mineral extraction often points to an understanding of a mining life cycle that includes phases such as contracting, exploration, production, and closure. To center temporality when analyzing mining suggests both prioritizing and rethinking the time scale that shapes ongoing discourses and practices regulating the sector. Paying attention to silenced time–space dynamics within the mining life cycle is a key aspect of centering temporality. Yet the emphasis placed on each phase is determined by vested economic interests that pay little attention to the long-term, negative environmental consequences embedded within the mining life cycle and are not linear. This chapter takes a critical look at the limited statehood and legal vacuum confronting the governance of large-scale mine closure in Africa. It asks whether and to what extent global, regional, and country-level mining governance frameworks fail to hold mining companies accountable for the long-term environmental destruction they cause. The analysis is informed by Upendra Baxis’s concept of “geographies of injustice,” which in this context are reproduced by obscuring a key spatiotemporal dimension in the mining cycle: the mine closure stage. Bringing together scholarship of environmental justice, comparative environmental politics, and global norms, the discussion focuses on mine closures in Africa to illustrate how legal structures and norms collude with the state to render certain aspects of capitalist interests invisible. Current policy silences are anchored within exclusive ontological premises, which in turn reproduce geographies of injustice across the extractive cycle.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".