La Voz del Pueblo: Maya Consultas and the Challenge of Self-Determination for Socially Responsible Investment in the Mining Sector.
Bibliographic record
Abstract
In Guatemala, the consulta comunitaria recently emerged as a process for local communities to resist mining and other extractive industries in the absence of government consultation.Approximately one million people in more than 76 of these plebiscites said "no" to mining or other extractive projects since 2005.This case study examines the perspectives of consulta organizers from three Maya communities in Guatemala's western highlands who rejected the presence of Canada's Goldcorp, Inc. Interviews between May and November 2010 asked the organizers about the movement and the role of Goldcorp's socially responsible investor (SRI), the Ethical Funds, to promote indigenous rights.Employing a critical geographic approach to examine the consultas as an exercise of power and indigenous self-determination, the analysis found that consulta organizers were motivated by the historic and ongoing exclusion of their communities from the priorities of government, the proximity of the mineral licenses to their communities and the potential negative environmental and social impacts from mining.The organizers had no knowledge of SRIs and the lack of knowledge reveals a corporate social responsibility (CSR) gap that is the product of asymmetrical information distribution between investors and affected communities.I conclude that the consultas challenge the discourse of CSR by demanding explicit respect for the right to free, prior and informed consent, and represent a boundary condition for CSR where a local action creates geographic limits on where CSR, as practiced by the mining industry, is welcome.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".