Nigerian Troops in the War Against Boko Haram: The Civilian–Military Leadership Interest Convergence Thesis
Bibliographic record
Abstract
This study interrogates the experiences of Nigerian troops in the war against Boko Haram. The paper’s contribution is bi-dimensional. First, it adds to the empirical literature on Boko Haram by analyzing the perspectives of rank-and-file troops. The study finds 10 forms of corruption affecting troops. These have contributed to the inability to defeat Boko Haram. Second, the paper adds to theoretical scholarship on civil–military relations and persistence of small wars. It challenges the bureaucratic-organizational model and the focus of civil–military relations theory on civilian control of the military. The study emphasizes the need to focus on the texture of the relationship between civilian and military leaders. The paper argues that the bureaucratic-organizational model has limited relevance to militaries in the postcolony and proposes a civilian–military leadership interest convergence thesis. The findings are relevant for understanding the spread of terrorism in sub-Saharan Africa and the persistence of small wars in non-Western, illiberal quasi-democratic societies.
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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 | 0.002 | 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 | 0.012 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".