Is collaboration possible between the small-scale and large-scale mining sectors? Evidence from ‘Conflict-Free Mining’ in the Democratic Republic of the Congo (DRC)
Bibliographic record
Abstract
Artisanal and small-scale mining (ASM) is an important livelihood activity for millions of people across the globe. Often, small-scale miners operate in, or adjacent to large-scale mining (LSM) concessions, potentially leading to conflict. Multilateral organizations and some governments have encouraged collaboration between ASM and LSM, prompting an academic debate over the risks and rewards of such approaches. This article argues that the local political economy of the mining sector is of crucial importance in determining the feasibility of ASM-LSM collaboration. In the Democratic Republic of the Congo (DRC) traceability schemes, intended to ensure that minerals and metals are ‘conflict-free’, are a major part of the political economy, and heavily influence local governance. Traceability schemes may be seen as a type of decentralized enclave economy. The article uses two case studies of ASM-LSM agreements in the DRC to explore how traceability may impact efforts at collaboration.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".