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Record W7078800564

The Curse of Coal Mining : Residents’ Resistance to Industrial Coal Mining in Moatize District, Mozambique

2025· article· en· W7078800564 on OpenAlexfundno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersPartenariat Canadien Contre Le CancerUppsala Universitet
KeywordsSubsistence agricultureCoal miningResistance (ecology)Government (linguistics)CurseState (computer science)Local governmentExpropriationCorporationMultinational corporation
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the dynamics and everyday practices of resistance in response to a large-scale coal mining project in Mozambiqueʼs Moatize District. The district underwent a significant territorial transformation after the Mozambican government granted the first coal mining concession to the Brazilian multinational mining company Vale in 2007. This concession encompassed vast areas of land traditionally used by local communities, who were subsequently displaced to make way for coal mining. The thesis is based on twelve months of anthropological fieldwork conducted in Moatize District. In this area, the mining company’s operations significantly affected local residents’ daily lives and means of subsistence. Most interlocutors were subsistence farmers and brickmakers who had been resettled by Vale in the 25 de Setembro neighbourhood within the Municipality of Moatize, as well as in the localities of Benga, Cateme and Mualádzi. The research also focused on traditional chiefs, traditional healers, state officials, informal traders, members of civil society organisations, and former CARBOMOC and CCM employees. Drawing on James Scott’s theoretical framework of everyday resistance, this thesis demonstrates how residents of Moatize adopted discreet, infrapolitical tactics to resist Vale’s mining practices and repression by state authorities. Using the limited resources at their disposal, they confronted a powerful corporation backed by the state. To expose the harmful effects of coal mining, residents shared images of mine explosions near their homes on social media, while protecting the identity of those who captured them. They also accessed forested areas on Vale’s land to gather resources essential for their livelihoods. In some cases, acts of resistance included invoking ancestral spirits through traditional healers to halt the tractors extracting coal from the mines. Overall, the thesis demonstrates that, despite seemingly powerless, the residents of Moatize asserted their agency by resisting the mining practices of the powerful multinational company Vale, which was backed by the central state.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.268
Teacher spread0.242 · 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
Published2025
Admission routes1
Has abstractyes

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