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Record W4200203233 · doi:10.1017/9781108961011

Black Markets and Militants

2021· book· en· W4200203233 on OpenAlexaff
Khalid Mustafa Medani

Bibliographic record

VenueCambridge University Press eBooks · 2021
Typebook
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsMilitantContext (archaeology)GlobalizationState (computer science)Political sciencePoliticsPolitical economyIdeologyExpatriateDevelopment economicsSociologyGeographyLawEconomics

Abstract

fetched live from OpenAlex

Understanding the political and socio-economic factors which give rise to youth recruitment into militant organizations is at the heart of grasping some of the most important issues that affect the contemporary Middle East and Africa. In this book, Khalid Mustafa Medani explains why youth are attracted to militant organizations, examining the specific role economic globalization, in the form of outmigration and expatriate remittance inflows, plays in determining how and why militant activists emerge. The study challenges existing accounts that rely primarily on ideology to explain militant recruitment. Based on extensive fieldwork, Medani offers an in-depth analysis of the impact of globalization, neoliberal reforms and informal economic networks as a conduit for the rise and evolution of moderate and militant Islamist movements and as an avenue central to the often, violent enterprise of state building and state formation. In an original contribution to the study of Islamist and ethnic politics more broadly, he thereby shows the importance of understanding when and under what conditions religious rather than other forms of identity become politically salient in the context of changes in local conditions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2021
Admission routes1
Has abstractyes

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