Are some minerals more governable? Copper mining materialities and formalization of artisanal and small-scale mining in Peru
Bibliographic record
Abstract
Artisanal and small-scale mining (ASM) is one of the main non-agricultural activities in the developing world, despite its often informal or illegal status. The formalization of ASM has been central in efforts to address the sector's challenges and enhance its potential for rural livelihoods. However, in Latin America, much of the academic and policy focus on ASM has been on gold mining, with standardized approaches to resource governance that overlook the sector's diversity. Such perspectives fail to address the distinct possibilities and constraints of formalization, which often vary depending on the mineral type and geological conditions. Based on extensive ethnographic and qualitative research in northern Peru, this article examines how the materiality of copper-rich mineral extraction has facilitated artisanal miners' progress in the formalization process. Without falling into geological reductionism, we argue that the material and geological properties of copper-rich deposits in some ASM mine sites can catalyze socio-political arrangements and technical transitions aligned with the goals of Peru's formalization policy. In line with this argument, we first show how copper's geological characteristics discourage the use of cyanide and mercury, thereby promoting more environmentally acceptable mining practices. Secondly, we explore how the necessity for deep mining in copper extraction encourages capitalization, technological innovation, and professionalization of mining activities. Finally, we discuss how security and logistical challenges involved in the transportation of large volumes of copper-rich raw minerals incentivize formalization. By focusing on non-gold ASM, this research contributes to a growing body of literature on the factors that influence formalization efforts, underscoring the pivotal role of resource materiality.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".