Oil Transnational Corporations and the Legacy of Corporate-Community Conflicts: The Case of SEEPCO in Nigeria
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".