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Record W6922123297 · doi:10.11575/prism/26825

Manipulating State Failure: Al-Shabaab's Consolidation of Power in Somalia

2015· other· en· W6922123297 on OpenAlexfundno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typeother
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaAfrican UnionGovernment of AlbertaAustralian GovernmentUnited States Agency for International Development
KeywordsNucleofectionGestational periodTSG101DiafiltrationHyporeflexiaLiquationDemotionProteogenomics

Abstract

fetched live from OpenAlex

This thesis addresses the question: How has Al-Shabaab’s position of power across large swaths of Somalia challenged assumptions about the organizational capacities of terrorist organizations within the context of state failure? At its core, this question is composed of four parts: an assessment of the power maintained by Al-Shabaab; an evaluation of the assumptions made about the operational abilities of such groups; an understanding how organizational capacity can be measured; and an assessment of state failure’s relationship to informal institutions and non-state actors. This research noted a significant shift in the capabilities of non-state actors attempting to consolidate power in Somalia as social and political contexts evolved over time. Such dramatic shifts exposed the specific circumstances necessary for the development of conditions that allowed for organizations, such as Al-Shabaab, to accumulate domestic power and authority, while extending their reach regionally.

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 score0.025
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.016
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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