Bibliographic record
Abstract
Abstract This is a history of precious-metals extractivism as lived in Cerro de San Pedro, a small gold- and silver-mining district in Mexico. Chronicling Cerro de San Pedro's operations from the time of the Spanish conquest to the present, Daviken Studnicki-Gizbert transcends standard narratives of boom and bust to envision a multicentury series of mining cycles, first operated under Spanish rule, then by North American industry, and today in the post-NAFTA world of transnational capitalism. The depletion of a mine did not mark the end of its life, it turns out. Evolving technology accelerated the flow of matter and energy moving through the extractive systems of exhausted mines and revived profitability over and over again in Mexico's mining districts. The book demonstrates how this serial reanimation of a non-renewable resource was catalyzed by capital and supported by state policy and ideology and how each new cycle imposed ever more harmful consequences on both laborers and natural ecologies. At the same time, however, miners and their communities pursued a contending vision—a moral ecology—that defended the healthy reproduction of life and land. This book's breathtakingly long view brings important perspective to environmental justice conflicts around extraction in Latin America today.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".