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Record W2030812494 · doi:10.1080/08941920.2013.861554

<i>Consultas</i>and Socially Responsible Investing in Guatemala: A Case Study Examining Maya Perspectives on the Indigenous Right to Free, Prior, and Informed Consent

2014· article· en· W2030812494 on OpenAlexaffabout
Julie Laplante, Catherine Nolin

Bibliographic record

VenueSociety & Natural Resources · 2014
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsMayaIndigenousLegitimacyIndigenous rightsCorporate social responsibilityInvestment (military)Informed consentPolitical scienceEconomic growthPublic relationsBusinessSocioeconomicsSociologyLawHuman rightsEconomicsMedicinePoliticsGeography

Abstract

fetched live from OpenAlex

Since 2005, more than 78 Maya communities representing approximately one million Guatemalans have held referendums called consultas comunitarias, which ask the community whether they are in agreement with mineral, hydroelectric, and/or other megaprojects in their traditional territory. Participation in the consultas is a form of resistance to the granting of mineral rights to corporate interests. In Canada, where much of the Guatemalan mining investment is based, “socially responsible investment firms” (SRIs) promote corporate respect for Indigenous rights. Based on interviews and participant observation, we highlight the perspectives of Maya consulta organizers in three communities that have undertaken consultas to resist the mining licenses of the Canadian mining company Goldcorp, Inc. We argue that a strict policy of corporate respect for the right to free, prior, and informed consent of affected communities is a minimum requirement for Maya acceptance of SRI legitimacy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0420.021
Scholarly communication0.0060.004
Open science0.0020.010
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.243
Teacher spread0.226 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2014
Admission routes2
Has abstractyes

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