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Record W4280517309 · doi:10.1111/apv.12345

Environmental justice and the politics of coal‐fired thermal power in Vietnam's Mekong Delta

2022· article· en· W4280517309 on OpenAlexaff
Nga Dao

Bibliographic record

VenueAsia Pacific Viewpoint · 2022
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsYork University
FundersNatural Environment Research CouncilSight Research UK
KeywordsLivelihoodEnergy securityIndustrialisationEcological modernizationNatural resource economicsModernization theoryPoliticsPopulationVietnamesePolitical scienceEconomic growthDevelopment economicsEconomic systemEconomicsRenewable energyGeographyEngineeringSociologyLaw

Abstract

fetched live from OpenAlex

Coal‐fired thermal power has recently become one of the most pressing issues in Vietnam's development agenda. The country's economic development, industrialization and modernization, and population increases have put increasing pressure on energy demands. The Vietnamese government sees coal‐fired power as a way forward in ensuring energy security, which had led to the planning and construction of plants nationwide, particularly from 2016. Simultaneously, a growing anti‐coal power development movement argues that coal‐fired power adversely transforms local people's lives and livelihoods, and negatively impacts the ecological balance in plant locations. Through the lens of environmental justice, this paper examines the development of Vietnam's power sector with a focus on coal‐fired thermal power and its impacts on local livelihoods, food production and water resources. The paper argues that Vietnam's development of coal‐fired power is about much more than energy. It speaks to the state's rule over resources, and how this very process of power generation disproportionately affects local communities in the Mekong Delta.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.009
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0010.002
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 head0.006
GPT teacher head0.180
Teacher spread0.175 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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