Dutch terrorist suspects 2004-2017 Vanja Ljujic & Fabienne Thijs

International terrorism in waves International Jihadi terrorism (cf. Gallagher, 2016) ‘Inspirational’ wave ‘Elite’ wave ‘Home grown’ wave ‘Gangsta’ wave Immigrants gangs (Europol) The crime terror nexus (Basra & Neumann, 2016; Ljujic, et al., 2017) 80% history of violent or petty crimes ‘sporadic’ criminals fragmentized cells prison radicalization & recruitment linear historical overview of the crime-terror nexus, viewed as a dynamic phenomenon, influenced by Zeitgeist 4th wave: detention centers often ‘dating-service’ for criminals and extremists

Theoretical background in steps Perceived threat (Stephan, 2014; Schmid & Muldoon, 2015) Strain (Agnew, 2016) Significance loss (Kruglanski, et al., 2014; Doosje, et al., 2015)

Unique data Dutch terrorist suspects (N 279), who were accused of ‘crimes with terrorist intent’ in the Netherlands (Terrorist Act 2004). Data from the Dutch prosecution office Data combined with several anonymous datasets on general statistics (CBS).

Table 1 Demographics, SES and criminality among terrorist suspects (Prosecution office and CBS data)   Demographics, SES & criminality Terrorist suspects (total) (n=279) Sex Male Female 87.5 % (244) 12,5 % (35) Age during offence 17 or younger 18 - 25 26 - 35 36 - 45 46 or older 7.9 % (22) 32.6 % (91) 30.5 % (85) 19.7 % (55) 9.3 % (26) Origin Non-immigrant 1st generation 2nd generation 18.6 % (52) 41.2 % (115) 40.1 % (112) Employment Yes No 39.4 % (110) 60.6 % (169) Criminal offences 21.9% (61) 78.1 % (218)

Table 2 Demographics, SES and criminality among terrorist suspects, general suspects and general population (Prosecution office and CBS data)   Demographics, SES & criminality Terrorist suspects (n=279) Other offenders General population Origin Non-immigrant 1st generation 2nd generation 18.6 % (52) 41.2 % (115) 40.1 % (112) 58.1 % (162) 24.7 % (69) 17.2 % (48) 70,3 % (196) 21.9 % (61) 7.8 % (22) Employed Yes No 39.4 % (110) 60.6 % (169) 49.8 % (139) 50,2 % (140) Education is sufficient for job No/unknown 15.1 % (42) 84.9 % (237) 24.0 % (67) 76.0 % (212) 43.0 % (120) 57.0 % (159) Criminal offenses 21.9% (61) 78.1 % (218) 100.0 % (279) 1.8 % ( 5 ) 98.2 % (274)

Table 3 Summary of Logistic Regression Analysis for Variables Predicting Terrorist Suspect (n=347) B (SE) Lower Odds Ratio Upper Immigrant origin 1.52 (0.14) *** 3.44 4.59 6.12 Work -.55 (.21) ** .38 .57 .86 Other offences 2.5 (.50) *** 4.58 12.25 32.8o Note: Terrorist suspect (coded 1 for yes and 0 for no). R2=.32 (Cox & Snell), .43 (Nagelkerke). *p < .05. **p < .01. ***p < .001. criminological implications of strain in general & instrumental use of violence in particular

Table 4 Demographics and SES among non-IS and IS-terrorist suspects (Prosecution office and CBS data) Terrorist suspects Before IS (N=123) During IS (N=156) Age at the time of terrorist offence 17 or younger 18 - 25 26 - 35 36 - 45 46 or older 9 (7%) 37 (30%) 26 (21%) 36 (29%) 15 (12%) 13 (8%) 54 (35%) 59 (38%) 19 (12%) 11 (7%) Origin Non-immigrant 1st generation 2nd generation 24 (19.5%) 67 (54.5%) 32 (26%) 28 (18%) 48 (31%) 80 (51%) Employment Yes No 63 (51%) 60 (49%) 47 (30%) 109 (70%) Criminal offenses 23 (19%) 100 (81%) 38 (24%) 118 (76%) Chi-Square statistics for: Age X²(4, N = 279) = 18.94, p > .001 Origin X²(2, N = 279) = 20.4, p > .001 Employment X²(1, N = 279) = 12.81, p > .001 Criminal offenses X²(1, N = 279) = 1,29, p=.25, ns

Attractive target audience for terrorist recruiters Second generation Unemployed With criminal past What does it mean in reality? Comparing the sample of the European group with Dutch samples reveals some interesting dissimilarities. All jihadi terrorists in the European sample are men. In contrast, at least a fourth of (both violent and terror offenders) in the Dutch sample are women. The two groups also differ with regard to age. These dissimilarities may, at least partly, be explained by measurement differences: Age of the Dutch sample was recorded at the time of violent crime and/or the time when persons attempted to or joined terrorist groups abroad. In contrast, European terrorists’ age was recorded at the time of attack. Many of them, including perpetrators of Brussels and Paris attacks have committed violent crimes or (attempted) to join ISIS at the age which is comparable with the Dutch sample

Policy implications Alternative, pro-social means for significance gain Employment may decrease the potential for crime and terror among disadvantaged groups Subtle criminal monitoring & prevention strategies in deprived districts Multicultural associations and community networks in support of mutual (interethnic and interreligious) understanding Needless to say, not all those who are poor and face adversity become terrorists or criminals. Neither is poverty a necessary characteristics of ideologically motivated violence. the socio-economic profile of crime and terror offenders have been evolving and changing over time disadvantageous youth are particularly at risk to be exposed to (and involved into) to all forms of violence in their immediate surroundings, such as family, neighbourhood and school.