Canadian Mining Interests in Bolivia, 1985–2015: Trajectories of Failures, Successes, and Violence
Bibliographic record
Abstract
Over the past decade there has been a growing interest in and concern about the actions of Canadian mining companies in Latin America. In this article we contribute to these debates by combining economic, social, and political analyses to examine the development of the Canadian government and the role of Canadian‐headquartered companies in Bolivia's mining industry. First, we review the influence of the Canadian government's development assistance on Bolivian mining policy. Second, we analyze the characteristics of Canadian FDI and its effects on the Bolivian mining sector. We argue that the economic effects of Canadian mining companies in Bolivia have been less than significant. We consider it a failed attempt, since our data suggests that the Canadian government attempted to “make Bolivia work” for mining companies. Finally, we illustrate the specific trajectories of Canadian mining companies with four brief case studies, two mines in operation, and two “failed attempts.” In the first two case studies we examine the development and accumulation of capital. In the second two cases, we focus on the social conflicts, which arose around the exploration activities of two junior mining companies. We argue that junior companies are important to consider when surveying the Canadian government's role in the country.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 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".