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Record W3014545396 · doi:10.1163/15691497-12341549

Capital Accumulation, Environmental Pollution, and Public Health Challenges in the Nigerian Petroleum Industry: Lessons on Market Criminology

2020· article· en· W3014545396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerspectives on Global Development and Technology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsBrock University
Fundersnot available
KeywordsExpansivePetroleumPetroleum industryNatural resourcePoliticsChevron (anatomy)Public healthGovernment (linguistics)Resource (disambiguation)EconomyEconomicsBusinessEconomic growthPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract Petroleum exploration activities started in Nigeria’s Niger Delta in the early twentieth century as part of the expansive process of primitive accumulation instituted by the British colonial administration to advance its economic interest. Since petroleum resources were discovered in commercial quantities in the region in 1956, transnational extraction corporations (including Shell, Chevron, and ExxonMobil) in collaboration with the emergent domestic compradors have plundered the resource wealth. While decades of crude oil and gas production in the region have enormously enriched the captors of the petroleum industry, the host communities have suffered debilitating economic and health consequences. This article discusses the public health challenges resulting from this predatory political economy, along the lines of a bourgeoning body of literature that conceptualizes preventable market-driven harms as criminal.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.133
GPT teacher head0.301
Teacher spread0.168 · 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