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Explaining Recruitment to Extremism: A Bayesian Hierarchical Case–Control Approach

Published online by Cambridge University Press:  16 November 2023

Roberto Cerina ,
Christopher Barrie Open the ORCID record for Christopher Barrie [Opens in a new window] ,
Neil Ketchley  and
Aaron Y. Zelin
Roberto Cerina*
Affiliation:
Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam, The Netherlands
Christopher Barrie
Affiliation:
Department of Sociology, University of Edinburgh, Edinburgh, UK
Neil Ketchley
Affiliation:
Department of Politics and International Relations, University of Oxford, Oxford, UK
Aaron Y. Zelin
Affiliation:
Brandeis University, Waltham, MA, USA
*
Corresponding author: Roberto Cerina; E-mail: r.cerina@uva.nl
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Abstract

Who joins extremist movements? Answering this question is beset by methodological challenges as survey techniques are infeasible and selective samples provide no counterfactual. Recruits can be assigned to contextual units, but this is vulnerable to problems of ecological inference. In this article, we elaborate a technique that combines survey and ecological approaches. The Bayesian hierarchical case–control design that we propose allows us to identify individual-level and contextual factors patterning the incidence of recruitment to extremism, while accounting for spatial autocorrelation, rare events, and contamination. We empirically validate our approach by matching a sample of Islamic State (ISIS) fighters from nine MENA countries with representative population surveys enumerated shortly before recruits joined the movement. High-status individuals in their early twenties with college education were more likely to join ISIS. There is more mixed evidence for relative deprivation. The accompanying extremeR package provides functionality for applied researchers to implement our approach.

Keywords

Bayesian analysisspatial autocorrelationrare eventsmultilevel modelingextremism
Type
Article
Information
Political Analysis , Volume 32 , Issue 2 , April 2024 , pp. 256 - 274
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Society for Political Methodology

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Footnotes

Edited by: Jeff Gill

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Supplementary material: Link

Cerina et al. Dataset

Dataset

https://doi.org/10.7910/DVN/HYOQCD
Link
Supplementary material: PDF

Cerina et al. supplementary material

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