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Improving the Evidence Base Supporting Counterterrorism Strategy: Heterogeneity across Contexts and Actors

Jul 18, 2018 @ 1:00 pm - 2:30 pm

Improving the Evidence Base Supporting Counterterrorism Strategy: Heterogeneity across Contexts and Actors

SPEAKER:  Christine Brugh



In this presentation, I review our efforts to improve the evidence base supporting risk factors for terrorism. Based on the results of our systematic review, several projects aimed at uncovering differences between across and across contexts will be described. First, I will discuss our work on gender differences using data from the Western Jihadism Project (WJP) (Klausen, 2018). In this work, I describe characteristics of female terrorists (N=405) and use a matched sample to test for differences in male and female terrorists (N=539). Analyses revealed differences in employment, education, criminality, and terrorist action/affiliation. Second, I will review the results of our analyses on differences in plot characteristics by geographic location. Overall, our findings contradict a one-size-fits-all counterterrorism approach and reinforce the need for research to inform risk assessment and models of radicalization across different contexts and actors.


WEB/CONFERENCECALL INFO: We are going to use the NC State WebEx for the web conference. Please note that this WebEx belongs to NC State and can not be downloaded directly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please join via computer and then have the meeting call your number or call in directly using one of the numbers below. When not speaking, please mute your phone to avoid background noise. When it’s time, join the WebEx meeting from here:




919-513-9329 (WolfMeeting)

Access Code: 996 474 981



Jul 18, 2018
1:00 pm - 2:30 pm


Partners I, 1017 Main Campus Dr, Raleigh, NC 27606, USA
800 Main Campus Dr United States



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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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