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Record W4220663192 · doi:10.1177/0095327x211072894

Nigerian Troops in the War Against Boko Haram: The Civilian–Military Leadership Interest Convergence Thesis

2022· article· en· W4220663192 on OpenAlex
Temitope B. Oriola

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArmed Forces & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsScholarshipBoko haramPolitical scienceBureaucracyCivil–military relationsTerrorismDemocracyPolitical economyCriminologyLanguage changeConvergence (economics)LawSociologyInsurgencyPoliticsEconomic growthEconomics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.085
GPT teacher head0.304
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it