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Record W2929148112 · doi:10.1093/jogss/ogy047

Population-Centric Counterinsurgency in the Age of Salafi-Driven Insurgencies

2018· article· en· W2929148112 on OpenAlex

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

VenueJournal of Global Security Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsInsurgencyPolitical scienceDoctrinePopulationArgument (complex analysis)State (computer science)Boko haramIdeologyGovernment (linguistics)Political economyCaliphateAdversaryCriminologySociologyLawPoliticsComputer securityMedicine

Abstract

fetched live from OpenAlex

Abstract This article explores the relevance of the dominant, population-centered, counterinsurgency doctrine in an era dominated by Salafi-inspired state challengers. Building on Weinstein's (2007) argument, I argue that an insurgent group's emergent nature, shaped by its origin, affects how it will operate and the kind of strategy most likely to defeat it. I investigate the plausibility of my claims through an examination of Boko Haram. I demonstrate the disconnect between Boko Haram's Salafi ideology and its objective of establishing a caliphate, on the one hand, and the strategy of dialogue and socioeconomic reforms to end the insurgency, on the other. In light of this disjuncture, I argue that the key to Boko Haram's defeat lies in the mobilization of international military and intelligence resources to strengthen the Nigerian government's enemy-centered counterinsurgency operation against the group.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.379
Teacher spread0.336 · 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