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Record W3160378873 · doi:10.4000/cal.11445

Alchemy in un mundo al revés: Gold, “Raw Law” and Indigenous Law in Colombia’s armed conflict

2020· article· fr· W3160378873 on OpenAlexaff
Viviane Weitzner

Bibliographic record

VenueCahiers des Amériques latines · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsSocial Sciences and Humanities Research Council
Fundersnot available
KeywordsIndigenousAlchemyLawIndigenous rightsSociologyHomelandInternational lawPolitical scienceEthnographyHuman rightsPoliticsAnthropologyHistory

Abstract

fetched live from OpenAlex

Using the concept of alchemy as a conceptual backbone, this article explores the effects of diverse legal pluralities on the Embera Chamí Indigenous people living in the gold-rich ancestral homeland of the Resguardo Indígena Cañamomo Lomaprieta in Caldas, Colombia. Drawing on ten years of collaborative research and ethnography, I develop a concept I call “Raw Law,” the law of outlawed, armed actors and their norms, sanctions and modus operandi, contributing insights that push conceptual boundaries and add complexity to analyses of “the law.” I show the “inter-il-legalities” at work, as the Embera Chamí exercise their own law over their self-named and centuries-old “ancestral mining,” as a counter-proposal and exercise of self-determination in the face of State Law that criminalizes this gold mining and attempts to impose unilaterally developed formalization schemes. I tease out the effects of “nefarious alchemical” technologies deployed to erode the Embera Chamí land base and constrain their autonomy and decision-making, highlighting the “positive alchemies” the traditional authorities use to assert their self-government and push for their rights to be upheld. I consider the types of transnational flows intruding on the Embera Chamí and what this distinct and violent context means for analysis through the lens of legal pluralities in Colombia, Latin America, and beyond.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.282
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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