Radicalization and Recruitment: A Systems Approach to Understanding Violent Extremism – New Developments Through FRAM

Radicalization and Recruitment: A Systems Approach to Understanding Violent Extremism – New Developments Through FRAM

Anthony J. Masys (University of Leicester, UK)
Copyright: © 2018 |Pages: 27
DOI: 10.4018/978-1-5225-5996-2.ch011

Abstract

As described in the GTI, ISIL's transnational tactics in combination with lone actor attacks inspired by the group drove an increase in terrorism to its highest levels ever across Europe and many OECD countries (upwards of a 650 percent increase in deaths since 2014). The attacks by ISIL in Paris, Brussels, and in Turkey's capital Ankara, were amongst the most devastating in the history of these countries and reflect a disturbing return of the transnational group-based terrorism. Actor network theory (ANT) was applied as a systems lens to open the “blackbox” of terrorism. The systems view facilitated by ANT highlighted how dynamic networked actors shape radicalization through the actor network process of translation. This chapter applies functional resonance accident model (FRAM) methodology. The FRAM method was used to analyze how radicalization activities (as described through ANT) take place and where and how intervention strategies can be designed to interfere with the radicalization process.
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Introduction

Recent events such as the terrorist attack in Algeria (January 2013), the Boston Marathon Bombing (April 2013), attacks in Paris (2016), Belgium (2016), Manchester (2017), UK (2017) highlight the requirement for greater understanding regarding the radicalization and recruitment of terrorists. As detailed in the US Department of State Report (2011), over 10,000 terrorist attacks occurred in 2011, affecting nearly 45,000 victims in 70 countries and resulting in over 12,500 deaths. With a focus on the outcomes and results of terrorist activities, terrorism itself often becomes a ‘blackbox’ concept that does not capture the essence of the radicalization process nor the mechanisms of recruitment. This conceptual paper introduces Actor Network Theory (ANT) as a systems lens to open the ‘blackbox’ of terrorism. This systems lens ‘…is a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static snapshots’ (Senge, 1990,p. 68). The systems view facilitated by ANT is supported and informed by methods of network analysis and conceptual modelling that highlight how dynamic networked actors shape the radicalization process through the actor network process of translation.

Terrorism is often labeled a global threat. The recent terrorist events highlight issues pertaining to recruitment, radicalization and supporting structures that enable terrorism worldwide. These events and others challenge our understanding regarding the impact of ideology and local context on the motivations and recruitment for terrorism. How do we collectively deal with such complex issues as terrorism, often termed ‘wicked problems’? The ‘fixes that fail’ archetype detailed by Senge (1990, 2006) and Sterman (2000) describe how action taken to rectify a situation, often only results in short term gains without addressing the foundational issues of the problem space. It forces one to revisit how we conceptualize ‘work as imagined’ in terms of terrorist activities and the actual ‘work as done’ (Hollnagel, 2012).

What is required in such wicked problems is greater understanding of the dependencies and interconnectivity that arises from a systems view of the problem space. This conceptual paper highlights actor network theory (ANT) as a systems lens to begin to reveal and unravel the complexities associated with terrorism and radicalization. In particular, the paper explores the application of the ANT process of Translation comprised of: problematization, interessement, enrolment and mobilization, to distinguish how heterogeneous becoming (Chia & King, 1998) of entities is reified within the context of terrorism and radicalization.

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