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Record W2982327022 · doi:10.1080/19392206.2019.1667052

“Weak State”, Regional Power, Global Player: Nigeria and the Response to Boko Haram

2019· article· en· W2982327022 on OpenAlexaff
David Mickler, Muhammad Dan Suleiman, Benjamin Maiangwa

Bibliographic record

VenueAfrican Security · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBoko haramState (computer science)CommissionPolitical sciencePolitical economyInsurgencyEliteInternational relationsTerritorial integrityPower (physics)Corporate governanceTerrorismInternal securityLawSociologyPoliticsSovereigntyEconomics

Abstract

fetched live from OpenAlex

Much of the literature explaining Nigeria’s failure to counter the Boko Haram insurgency since 2009 has focused on the country’s internal governance, drawing on variations of the “weak state” concept. In this article, we argue that analysts also need to examine Nigeria’s international relations for a more critical explanation of why it took over five years to eventually halt the violent group’s territorial expansion and regular commission of atrocities. Through analysis of primary documents from various institutions involved in responding to Boko Haram between 2010 to 2015, and elite interviews with academics, security officials and other analysts, this article argues that Nigeria’s relatively powerful regional and global positions effectively precluded coercive international intervention and, in doing so, reduced external pressure on Abuja to act more decisively to counter this major threat to security at the human, national and regional levels. Thus, we demonstrate that so-called “weak” states that are simultaneously powerful internationally can manage pressure for action on violence occurring inside their borders.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.290
Teacher spread0.281 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2019
Admission routes1
Has abstractyes

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