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“The Situation Will Most Likely Turn Ugly”: Corporate Counter-Insurgency and Sexual Violence at a Canadian-Owned Mine in Guatemala

2023· article· en· W4387168535 on OpenAlex
Simon Granovsky-Larsen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNorteamérica · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsInsurgencyElitePolitical scienceMayaCriminologyPublic relationsSociologyLawGeographyArchaeologyPolitics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.200
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it