DISASTER CAUSATIVE AGENTS: AN EXAMINATION OF THE SOCIAL AND POLITICAL CONTEXT IN THE NIGER DELTA REGION
Bibliographic record
Abstract
Disasters as phenomena, to a greater extent, are created whether they are natural or technological. There are causative agents that are implicated in every disaster. Disasters are incubated by these agents acting independently or collectively. The agents could be social, political, environmental or underdevelopment factors. How the agents act individually and collectively to create disaster depends on the context within which they occur. The Niger Delta region has experienced multiple disasters over a prolonged period of time. These disasters range from oil spills that led to community responses of various dimensions to the more recent militancy by agitated community members which created a different type of disaster, leading to loss of lives and wanton destruction of properties. This paper will show that the disasters have been largely influenced by social and political elements at play in the Niger Delta region. How the elements contributed in creating the disasters within the context of the Niger Delta region is the focus of this paper. This paper analyzes the social and political dynamics in the Niger Delta region, and explain how they have acted individually and collectively to influence the disasters in the region. It also identifies who the key actors are and what their roles are in creating the disasters. The events and happenings in the Niger Delta region are documented in academic papers, news articles and other reports. This paper examines these sources to determine the social and political elements that were at play within the Niger Delta region from the 1950s, when oil operations began, to the present day. It concludes with recommendations on how to mitigate such situations in future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".