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Record W4313990819 · doi:10.57054/ad.v47i4.2982

Modernisation minière, fragmentation sociale et création des anormaux en République démocratique du Congo

2023· article· fr· W4313990819 on OpenAlexaboutno aff
Emery Mushagalusa Mudinga, Janvier Kilosho Buraye, Anuarite Bashizi

Bibliographic record

VenueAfrica Development · 2023
Typearticle
Languagefr
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesModernization theoryArt

Abstract

fetched live from OpenAlex

L’article part du cas d’étude de la chefferie de Luhwindja – une collectivité située à l’est de la RDC – où, depuis l’année 2005, est mis en oeuvre un programme de modernisation minière à travers la multinationale canadienne dénommée Banro. Au-delà de ses effets sur les conditions de vie des populations locales et leur environnement, l’article rend compte de la manière dont la modernisation minière a reconfiguré les dynamiques sociales locales et transformé le rapport des populations locales à l’autorité. D’où l’on déduit le caractère d’une modernité insécurisée. Se basant sur les entretiens, les discussions en groupe, l’observation et l’expérience des auteurs, l’étude renseigne que la modernisation minière, en ayant promu l’investissement privé et attiré des entreprises capitalistes dans les régions minières en RDC, ces dernières ont déstructuré les équilibres de pouvoir existant dans l’arène locale, et ce, par la répression et l’instrumentalisation des luttes sociales locales existantes. C’est cette logique de diviser pour régner – susceptible de contribuer et de renforcer la fragmentation sociale – qui a alors rendu possible le processus de modernisation minière malgré toutes les stratégies de résistance des populations dans les zones concernées en République démocratique du Congo.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.007
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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