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Record W2767155844 · doi:10.1017/s0001972017000365

Mobilizing the past:<i>creuseurs</i>, precarity and the colonizing structure in the Congo Copperbelt

2017· article· en· W2767155844 on OpenAlexaff
Timo Makori

Bibliographic record

VenueAfrica · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsColonialismPrecarityState (computer science)LiberalizationNeoliberalism (international relations)ModernitySovereigntyPolitical sciencePolitical economyDevelopment economicsSociologyPoliticsLawEconomics

Abstract

fetched live from OpenAlex

Abstract The Copperbelt of Congo was once the bastion of industrial development and no individual embodied its modernity as fully as the salaried industrial miner. Today, with the near collapse of the state-run mining company, Gécamines, and the liberalization of the mining industry starting in 2002, the majority of miners are no longer trained and salaried industrial workers but rather children and youth eking out a precarious living as artisanal miners or creuseurs . In Congo, artisanal mining is paradoxical, for, although it indexes a future of unskilled, untrained, flexible work in rural and peri-urban enclaves, its organization of labour and rudimentary techniques of copper extraction allude to and borrow from the colonial and precolonial past. Creuseurs mobilize the past as a strategic response to the threat of dispossession of ‘their’ land by the state and foreign investors, and they do so by laying claim to an anterior ‘sovereign’ – the ancestors – whose existence predates colonialism. This paradoxical emplacement of artisanal mining, its entanglement in time, invites interrogation of some of the ways in which scholars have understood precarity not only as a politically induced condition resulting from neoliberalism but also as an outcome of the enduring nature of the colonizing structure in Africa.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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

Citations33
Published2017
Admission routes1
Has abstractyes

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