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Record W3176068986 · doi:10.17230/co-herencia.18.34.6

Drug-Trafficking in Colombia: The New Civil War Against Democracy and Peacebuilding

2021· article· en· W3176068986 on OpenAlexaff
María-Paula Espejo

Bibliographic record

VenueCo-herencia · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicConflict, Peace, and Violence in Colombia
Canadian institutionsWestern University
Fundersnot available
KeywordsDemocratizationPolitical scienceDemocracyTransitional justicePhenomenonPeacebuildingPoliticsCriminologyLaw and economicsSociologyLawPolitical economy

Abstract

fetched live from OpenAlex

Drug-trafficking in Colombia has been a widely researched phenomenon, especially now, as the country undergoes a transition process with its older guerrilla. Now more than ever it is fundamental to examine how drug-trafficking organizations violent activities affect the consolidation of peace. This article considers different approaches to study violence derived from drug-trafficking, in order to advance towards the objectives of transitional justice. For that matter, this work is based on the idea that drug-trafficking directly generates and reproduces violence which is fueled by the structural violence present in the Colombian context. My thesis is that this phenomenon deters non-repetition guarantees and weakens democracy, which is why there will be three main arguments presented that will revolve around the lack of consensus and the implications of considering drug wars as civil wars, how decisions related to the conceptual apprehension limit the competence of international humanitarian law, and the need for holistic strategies capable of facing drug-trafficking’s political and violent power. Later, alternatives will be explored around the possibilities that each argument offers, as well as which aspects could contribute to a more appropriate approach to combat drug-trafficking. Lastly, I will defend why implementing bottom-up oriented actions can advance towards transitional justice’s intermediate and final objectives, as it is the only alternative that escapes fatalist, utopian or interventionist scenarios.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.025
GPT teacher head0.316
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations5
Published2021
Admission routes1
Has abstractyes

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