Shell–NGO Partnership and Peace in Nigeria: Critical Insights and Implications
Bibliographic record
Abstract
The recent efforts to better understand how businesses can contribute to peace in conflict zones suggest that partnerships can be an effective vehicle for corporate peacebuilding. However, empirical analyses of how partnerships contribute to peace remain limited. Drawing on the differences among cultural, structural, and direct violence, this article examines the extent to which the partnership between Shell and a group of NGOs contributes to peace in the Niger Delta region. Based on qualitative data, the article shows that the partnership contributes to conditions that might ameliorate cultural sources of violence, but not structural causes of direct violence. Hence, business–NGO partnerships are likely more suitable for conflict prevention rather than conflict resolution. The implication is that while partnership might be a useful corporate peacebuilding strategy, it is not necessarily a panacea. The article identifies areas of future research that can strengthen the emerging field of business and peace.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.021 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".