Blood Economy: The Failure of the Developed World to End Conflict Minerals in the Congo
Bibliographic record
Abstract
Conflict minerals have long been among the leading causes of violence in part of the Global South. For many years there was little attention to the issue despite an enormous dependence on conflict minerals by advanced and emerging economies. In recent years however it seems that countries of the Global North have finally begun to take notice. Despite this attention efforts rarely equal success and the attempts by the developed world to end or reduce the trade in conflict minerals are no exception. The Kimberley Process, arguably the most successful effort so far, has generally been decried as ineffective and unproductive by several NGOs and some governments. This paper examines the issue of conflict minerals, their relationship with war and violence, and their role in the global economy in order to explain the failure of the developed world to end the trade of conflict minerals. The paper seeks to understand the lack of international attention to some of the worst atrocities since the holocaust and explores recently attempted solutions and the obstacles therein. The Democratic Republic of the Congo is used as a case study as the Second Congo War and the continuing violence in the country illuminate the murky complexities of the conflict mineral trade, from raw minerals to finished products.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".