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Record W3107182615 · doi:10.1017/s0022278x20000245

Ghana's petroleum industry: expectations, frustrations and anger in coastal communities

2020· article· en· W3107182615 on OpenAlexaff
Jesse Salah Ovadia, Jasper Abembia Ayelazuno, James Van Alstine

Bibliographic record

VenueThe Journal of Modern African Studies · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLivelihoodUnderdevelopmentPetroleum industryPetroleumAngerField researchPolitical scienceEconomic growthGeographyDevelopment economicsEconomicsSociologyEngineeringPsychologyAgricultureSocial science

Abstract

fetched live from OpenAlex

ABSTRACT With much fanfare, Ghana's Jubilee Oil Field was discovered in 2007 and began producing oil in 2010. In the six coastal districts nearest the offshore fields, expectations of oil-backed development have been raised. However, there is growing concern over what locals perceive to be negative impacts of oil and gas production. Based on field research conducted in 2010 and 2015 in the same communities in each district, this paper presents a longitudinal study of the impacts (real and perceived) of oil and gas production in Ghana. With few identifiable benefits beyond corporate social responsibility projects often disconnected from local development priorities, communities are growing angrier at their loss of livelihoods, increased social ills and dispossession from land and ocean. Assuming that others must be benefiting from the petroleum resources being extracted near their communities, there is growing frustration. High expectations, real and perceived grievances, and increasing social fragmentation threaten to lead to conflict and underdevelopment.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.006
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.251
Teacher spread0.202 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

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