1. Dutch terrorist suspects 2004-2017
Vanja Ljujic & Fabienne Thijs

2. 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

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

4. 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).

5. 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
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)

6. 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)

7. 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

8. 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
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

9. 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

10. 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.