“The Situation Will Most Likely Turn Ugly”: Corporate Counter-Insurgency and Sexual Violence at a Canadian-Owned Mine in Guatemala
Bibliographic record
Abstract
This paper offers a window into the terrain of corporate influence over violence in the mining industry. The research draws on over 300 pages of internal communications and other corpo-rate documents, which were produced by Vancouver-based Skye Resources and released pub-licly as an affidavit in a civil court case in Ontario, Canada. The documents demonstrate the roles of mining company executives and their collaborators in coordinating events that led to the gang rape of eleven Maya Q’eqchi’ women in Guatemala during a 2007 land eviction. Ana-lyzing the documents through a framework of corporate counter-insurgency (co-COIN), the pa-per explores the importance of international consultants and local elite networks in co-COIN campaigns. The case study explored in this paper contributes to the theorization of public-pri-vate repressive forces within co-COIN. The research also offers a visual tool to map actors in other instances of mining violence, which is intended for use by both academic researchers and anti-mining social movements.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".