Vandalization of Oil Pipelines in the Niger Delta Region of Nigeria and Poverty: An Overview
Bibliographic record
Abstract
The paper highlights pipeline vandalization and how it affects the oil communities in the Niger Delta, her food production and most importantly is the environmental effects of oil exploration in terms of the socio economy of the people, this paper focuses on how vandalization of pipeline as a manifestation of poverty in the Niger Delta. The act of destroying or bursting of oil pipelines in Niger Delta region is as a result of underdevelopment and fatal negligence of the well fare of the people by the federal and state government, oil pollution which occurs in the form of water contamination through oil spillage which results in very low fish catch, considering that this region has lost her farmland because of environmental; degradation through oil exploration, and oil exploitation. As a result of the complete neglect of these communities, poverty has become endemic in the Niger-Delta and its manifestation is in the incessant vandalization of oil pipelines, the various fire incidence that occurred at Jesse, 1998, Ovirri court 2000, others and their aftermath. Lastly, there is an attempt by this paper to state the federal government palliative programmes like OMPADEC and most recently, the Niger Delta Development commission (NDDC). Key words : Vandalization; Oil pipeline; Poverty; Niger Delta
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".