Lost in Corporate Translation: How Firms Mediate Between Social Mobilization and Regulatory Intervention in the Extractive Sector
Bibliographic record
Abstract
ABSTRACT Firms should be considered as actors that potentially mediate between social movement pressures and policy outcomes. This article shows that at the mining project level, social mobilization can generate important changes in corporate practices toward nearby communities, and that these practices can undermine the cohesion of social movement coalitions advocating for regulatory intervention or reform, thus limiting their ability to make compelling claims on the state. In this way, company interpretations of and responses to protest are an important mediating process that conditions civil society efforts to activate state institutions in their favor. This argument extends recent work on the social foundations of regulation in Latin America by including corporate actors. The article is based on a comparative case study of the Pascua Lama/Veladero mining projects in both Argentina and Chile, using both secondary sources and primary field research.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".