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Record W2992909773 · doi:10.21810/jicw.v2i2.1062

Handling the Iraqi Popular Mobilisation Forces In The Post-Islamic State Iraq

2019· article· en· W2992909773 on OpenAlexvenueno aff
Faisal Paktian

Bibliographic record

VenueThe Journal of Intelligence Conflict and Warfare · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsIslamState (computer science)Political scienceGovernment (linguistics)Public administrationPolitical economyLawSociologyGeographyComputer science

Abstract

fetched live from OpenAlex


 
 
 This article examines the future of the Iraqi Popular Mobilisation Forces the Islamic State of Iraq and Syria (ISIS) in Iraq. The PMF is militias that assisted the coalition forces in liberating Iraqi cities from ISIS control. However, in the aftermath of that operation, the PMF now poses a major threat to the future of state-building (PMF) after the fall of an umbrella organization of armed in Iraq. Their armed strength and loyalties to leaders other than the Iraqi government, combined with evidence from existing research on pro-regime militias, suggest that the PMF poses a high- threat in an unstable environment if not managed carefully. Therefore, this article addresses the following question: What can be done with the various militias of the PMF to ensure a secure and sustainable future in Iraq? The Iraqi government has already taken the first steps to mitigate the PMF’s threat by integrating them into the national army, but further integration is required. Since undergoing any disarming, demobilizing and reintegrating (DDR) program is unlikely in Iraq at present, this article recommends employing the PMF for the purpose of infrastructure reconstruction or its support.
 
 

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 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 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 score0.321

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.316
Teacher spread0.287 · 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 teacher head, 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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

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