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Record W4390274052 · doi:10.1515/ldr-2023-0083

Oil Transnational Corporations and the Legacy of Corporate-Community Conflicts: The Case of SEEPCO in Nigeria

2023· article· en· W4390274052 on OpenAlexaff
Martin-Joe Ezeudu

Bibliographic record

VenueThe Law and Development Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsLakehead University
Fundersnot available
KeywordsResource curseIndigenousNatural resourcePoliticsState (computer science)Political economyCorporate governancePetroleum industryMainstreamAppropriationPolitical scienceSociologyLawEconomicsManagementEcologyEngineering

Abstract

fetched live from OpenAlex

Abstract This paper examines the nature, impact, ramifications, and root causes of the corporate-community resource conflict in Anambra’s oil-bearing communities. It approaches this objective from the standpoint that such a conflict may be appropriately termed “a legacy of oil transnational corporations” in Nigeria, given their antecedents in the Niger Delta region. Unlike the existing literature that blames such conflicts for the most part on environmental, socio-economic, and political factors, with limited emphasis on the legal factors, this paper takes the position that an unhealthy legal apparatus of the Nigerian state and regulatory gaps in Nigeria’s oil industry provide the enabling environment that makes the conflict inevitable. Essentially, this paper tweaks the “resource curse” theory as espoused by mainstream political economists by demonstrating that, apart from greed and grievance, the “curse” is equally underpinned by inept legal structures and regulatory gaps that show little regard for good governance and the well-being of the local people in host communities. But two possible solutions are proffered. One is the institutionalization of a statutory scheme for consultation with the local communities before appropriation of their lands for oil production projects, and the other is encouraging the participation of indigenous peoples or indigenous entities in the development of their natural resources, following the example of Orient Petroleum Resources Plc.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.082
GPT teacher head0.251
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

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 designTheoretical or conceptual
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

Citations5
Published2023
Admission routes1
Has abstractyes

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