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Record W4297361126 · doi:10.1016/j.exis.2022.101163

Is collaboration possible between the small-scale and large-scale mining sectors? Evidence from ‘Conflict-Free Mining’ in the Democratic Republic of the Congo (DRC)

2022· article· en· W4297361126 on OpenAlexafffund
Chris Huggins

Bibliographic record

VenueThe Extractive Industries and Society · 2022
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLivelihoodTraceabilityDemocracyScale (ratio)GlobePoliticsCorporate governancePolitical scienceBusinessPolitical economyEconomyEconomicsGeographyEngineeringAgricultureLaw

Abstract

fetched live from OpenAlex

Artisanal and small-scale mining (ASM) is an important livelihood activity for millions of people across the globe. Often, small-scale miners operate in, or adjacent to large-scale mining (LSM) concessions, potentially leading to conflict. Multilateral organizations and some governments have encouraged collaboration between ASM and LSM, prompting an academic debate over the risks and rewards of such approaches. This article argues that the local political economy of the mining sector is of crucial importance in determining the feasibility of ASM-LSM collaboration. In the Democratic Republic of the Congo (DRC) traceability schemes, intended to ensure that minerals and metals are ‘conflict-free’, are a major part of the political economy, and heavily influence local governance. Traceability schemes may be seen as a type of decentralized enclave economy. The article uses two case studies of ASM-LSM agreements in the DRC to explore how traceability may impact efforts at collaboration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.035
GPT teacher head0.243
Teacher spread0.208 · 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 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

Citations16
Published2022
Admission routes2
Has abstractyes

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