library(ggplot2)
library(ggpattern)
# remotes::install_github("coolbutuseless/flagon")
# if(!require("sf")) {install.packages("sf"); library("sf")}
library(flagon)
<- c('at','be','bg','cz','ee','fi','fr','de','gr','hu','it','lv','nl','pl','ro','sk','si','es','gb')
country_codes
<- flags(country_codes, 'svg')
j
<- c(1990,1992,1993,1993,1994,1994,1995,1996,1997,1997,1998,1998,2000,2000,2001,2003,2004,2005,2005,2005,2006,2006,2006,2007,2008,2009,2009,2009,2009,2010,2011,2011,2012,2013,2013,2014,2014,2014,2014,2014,2015,2016,2016,2017,2019,2019,2019,2019,2019,2020,2020,2020,2020,2020,2020,2021,2021,2021,2022)
year <- c("Netherlands","Germany","Germany","Italy","Germany","Hungary","Germany","Germany","France","Germany","Germany","Netherlands","Germany","Italy","Germany","Germany","Belgium","France","Germany","Hungary","France","Germany","Slovakia","Germany","Germany","Estonia","Germany","Hungary","Poland","Czechia","Germany","Spain","Germany","France","Germany","Belgium","Germany","Hungary","Latvia","Romania","Germany","Germany","UnitedKingdom","UnitedKingdom","Austria","France","Germany","Poland","Slovenia","Bulgaria","Finland","France","Germany","Greece","UnitedKingdom","France","Germany","UnitedKingdom","France")
country <- c(1,4,3,3,1,1,3,1,2,1,1,1,2,1,1,1,1,1,4,1,1,2,1,1,2,1,3,1,1,1,2,2,6,5,2,1,3,1,1,1,2,3,1,2,1,2,1,1,1,1,1,1,3,1,3,2,1,3,1)
bans <- data.frame(year,country,bans)
preo_year_trim
if (require("magick")) {
ggplot(preo_year_trim) +
geom_col_pattern(
aes(x = year, y = bans, pattern_filename = country), colour="black", fill="gray70",
pattern = 'image',
pattern_type = 'fit',
pattern_scale = 1
+
) scale_pattern_filename_discrete(choices = j) +
scale_pattern_discrete(guide = guide_legend(nrow = 1)) +
theme_bw() +
scale_x_continuous("Year", breaks = seq(1990,2022,1), minor_breaks = seq(1990,2022,1)) +
scale_y_continuous("RWE Organisations Proscribed", breaks = seq(0,10,1), minor_breaks = seq(0,10,1)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1, size=11),
axis.text.y = element_text(size = 11),
axis.title.y = element_text(size = 11),
legend.text=element_text(size=11),
legend.title=element_blank(),
legend.position="bottom")
}
In a recent article in Terrorism and Political Violence, co-authored with Michael Vaughan and based on data collection with over 40 country experts (listed below), I presented and offered an initial analysis of a new dataset on proscribed right-wing extremist organisations (PREOs) in Europe. The dataset (up-to-date) includes 191 proscribed organisations. A version of the dataset is availble for download on my Data page, along with further information about the proscribed organisations. The data helps to fill a gap of comparative data and analysis on responses to RWE. It is my profound hope that the data will facilitate more research in this area. Here, I will summarise the analysis put forward in the article and provide (replicable) visualisations of the data.
As Michael (V.) and I write in the article, violent incidents in recent years have drawn public and political attention to the threats posed by RWE. “From terrorist attacks, to extremist riots at national and regional legislatures, to the quotidian menace of RWE assault and harassment—numerous countries are simultaneously shocked by and inured to the dangers of RWE.” States, often compelled to take action by public outrage and civil society advocacy, have occasionally turned to one of militant democracy’s most severe measures to counter extremism: proscription. Yet there is a conspicuous difference in the frequency that states have resorted to this measure. “Some states have proscribed right-wing extremist (RWE) organisations quite often, while others have used proscription laws only in isolated cases; still others eschew completely such legal instruments.” Where, how frequently, against which RWE organisations, and why have proscriptions been applied? Research has not attended to this puzzle. Before delving into questions of why some organisations are proscribed, we must first establish the descriptive basis for causal questions.
Organisational proscription takes place in one of two ways: through executive decree or judicial ruling. Juxtaposing these two modes with the number of instances in which they have been applied, as in Table 1, reveals differences among European countries’ proscription regimes. While the extent and weight of advisory input is uncertain, we can say that the proscription by executive decree is essentially a political decision, an action authorised by a party politician acting as the head of a governmental branch (typically the interior ministry). By contrast, the judicial mode, represented on the right-hand side of Table 1, typically involves the state or governmental actors bringing suit against a RWE organisation—but a court is the authority that deems that organisation illegal.
Executive decree | Judicial ruling | |
---|---|---|
highly active | Germany (54) France (13) United Kingdom (9) |
|
active | Italy (4) Hungary (1) Austria (1) Estonia (1) |
Hungary (3) Belgium (2) France (2) Netherlands (2) Poland (2) Spain (2) Bulgaria (1) Czechia (1) Finland (1) Greece (1) Latvia (1) Romania (1) Slovakia (1) Slovenia (1) |
inactive | Croatia, Cyprus, Denmark, Ireland, Lithuania, Luxembourg, Malta, Portugal, Sweden |
Close readers will notice that two countries are listed twice in Table 1. France and Hungary have applied both modes of proscription. In France, proscription typically occurs through executive decree, but two unions affiliated with the radical right Front National were outlawed by the high court partially on the basis that the unions were discriminatory. Conversely, in Hungary, court rulings have been the more common proscription mode. However, in 1994 an executive decree proscribed the Hungarian Hungarianist Movement (Magyar Hungarista Mozgalom), the first organisation proscribed in the post-communist era.
Table 1 shows that Germany has been the state most actively proscribing RWE organisations since 1990—which should not come as a surprise—followed by France and the United Kingdom. But these proscriptions are not evenly spread throughout the last 30 years. Figure 1 shows several spikes in proscription. In France, the proscription of RWE organisations in 2013 and 2019–2022 preceded significant reductions in right-wing violence. Simultaneously, the prominence of a far-right political party (the Front National) seems to mollify some extremists and mitigate violent actions, albeit by accepting greater radicalism in the sphere of party politics. The UK, which has only recently started proscribing RWE groups, banning National Action in 2016, has been the most active state in recent years.
Figure 1 suggests that proscription is becoming a more commonly used tool to disrupt RWE. There has been a slight increase in the number of organisations proscribed and in the array of countries using proscription. As we write in the article:
Several countries that have rarely (if ever) used proscription seem to be shifting their position: in Denmark, notwithstanding a long tradition of emphasizing and ensuring broad freedom of association, a law passed in 2016 (the “Act amending the Public Education Act and the Tax Act, Public Information Law”) opened the way for the proscription of a gang (Loyal to Familia);1 in the Netherlands in June 2021, “the Upper House of the legislature passed a law on anti-democratic organisations, giving judges the power to proscribe extremist organisations, prevent their leadership from running new organisations, and jail members that continue to be active for proscribed organisations”;2 and in Sweden an all-party committee has recently suggested amending the criminal code to impose penalties on racist organisations and their participants, that is, a form of proscription.3 Proscription may yet become a more widely used means of disrupting RWE activity.
RWE violence and organisational proscription
While the pecise conditions that are relevant for proscription are somewhat elusive, violence is surely among them. The right-wing terrorism and violence (RTV) dataset comprises information on attacks and plots motivated by right-wing extremist beliefs. Figure 2 plots side-by-side rates of RWE violent incidents, fatalities, and proscription. The resulting patterns are not suggestive of a close connection. Yet a connection does exist, as evinced by several noteworthy cases. The Finnish Supreme Court cited violence by longstanding activists of the Nordic Resistance Movement in justifying their proscription decision in 2020. Similarly, in Greece, despite the absence of a “constitutional option to ban political parties once they have been authorised to participate in elections,” the Criminal Court of Appeals in Athens made the unprecedented decision in 2020 to proscribe Golden Dawn;4 most prominent among the justifications were several conspicuous violent incidents, including the murder of anti-fascist activist Pavlos Fyssas in 2013.
library(ggplot2)
<- c(2000,2000,2001,2001,2002,2002,2004,2004,2005,2005,2007,2007,2008,2008,2009,2009,2010,2010,2012,2012,2013,2013,2016,2016,2016,2017,2017,2017,2020,2021,2000,2000,2003,2003,2004,2004,2005,2005,2007,2007,2011,2016,2016,2012,2012,2013,2013,2017,2017,2018,2018,2020,2002,2002,2005,2006,2010,2010,2013,2013,2013,2019,2019,2019,2020,2021,2016,2016,2020,2002,2002,2004,2006,2006,2014)
year <- c("UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","UnitedKingdom","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Spain","Greece","Greece","Greece","Greece","Greece","Greece","Greece","Greece","Greece","France","France","France","France","France","France","France","France","France","France","France","France","France","France","Finland","Finland","Finland","Belgium","Belgium","Belgium","Belgium","Belgium","Belgium")
country <- c(1,1,1,1,1,1,3,3,1,1,3,3,3,3,1,1,2,2,1,1,1,1,1,2,2,1,1,2,3,3,4,4,1,1,1,1,1,1,1,1,2,1,1,2,2,2,2,1,1,1,1,1,2,2,1,1,1,1,2,2,5,1,1,2,1,2,1,1,1,1,2,1,2,3,1)
number <- c("incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","ban","ban","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","ban","ban","incident","fatalities","incident","fatalities","ban","incident","fatalities","ban","ban","ban","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","ban")
type
<- data.frame(year,country,number,type)
PREORTV
<- ggplot(PREORTV, aes(x = year, y = number, fill = type)) +
country_selection geom_col(width = 1, position = position_dodge2(preserve = "single", padding = 0), color = "black", size = 0.2) + facet_wrap(~ country,ncol=3) +
scale_fill_manual(values = c("ban"="red", "incident"="lightblue", "fatalities"="black")) +
scale_x_continuous("Year", breaks = seq(2000,2021,2)) +
scale_y_continuous("", breaks = seq(0,6,1), minor_breaks = seq(0,6,1)) +
theme_bw() +
theme(strip.text.x = element_text(size = 12, colour = "black", angle = 0)) +
theme(legend.position="bottom", legend.title=element_blank(), legend.text=element_text(size=11),
axis.text.x = element_text(size = 11, angle = 90, vjust = 0.5, hjust=1),
axis.text.y = element_text(size = 11))
country_selection
Practices and trends in Germany
Of all European states, Germany has imposed proscriptions on RWE organisations most frequently. Figure 3 shows that 25 RWE organisations were banned between 1951 and 1956.5 Since the 1990s, 54 RWE organisations have been proscribed in Germany.
library(ggplot2)
library(scales)
<- c(seq(1950, 2021, by=1))
year <- c(0,2,7,11,1,0,3,0,0,0, # 1950s
PREOs 2,0,1,0,0,0,2,0,0,1, # 1960s
0,0,0,0,0,0,0,0,0,0, # 1970s
1,0,1,2,1,0,0,0,0,1, # 1980s
0,0,4,3,1,3,1,1,1,0, # 1990s
2,1,0,1,1,4,1,1,2,3, # 2000s
0,2,6,1,4,2,3,0,0,1, # 2010s
4,1) # 2020s
<- data.frame(year,PREOs)
df
<- ggplot(df, aes(x=year, y=PREOs)) +
DEtimeseries geom_bar(stat = "identity", width=0.8, fill='black') +
theme_bw() +
scale_y_continuous("Proscribed Right-wing Extremist Organisations", breaks = seq(0,12,1)) +
scale_x_continuous("Year", breaks = seq(1950,2022,2)) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1, size=12),
axis.text.y = element_text(size = 11),
axis.title.y = element_text(size = 11))
DEtimeseries
There does appear to be a relationship between the rates of proscription and right-wing terrorist incidents and fatalities, as in Figure 4, and more broadly violent right-wing crimes as recorded by German state security agencies, as in Figure 5. Spikes of violence in the early 1990s, the late 2000s, and during and after the refugee crisis in 2015–2016 were all met with several proscriptions.
library(ggplot2)
<- c(2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2004,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2007,2007,2007,2007,2007,2007,2007,2008,2008,2008,2008,2008,2008,2008,2009,2009,2009,2009,2009,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2013,2013,2013,2013,2013,2013,2013,2013,2014,2014,2015,2015,2015,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2016,2017,2017,2017,2017,2017,2017,2017,2018,2018,2018,2018,2019,2019,2019,2019,2019,2019,2020,2020,2020,2020,2020,2020,2020,2020,2020,2021,2021,2021,2021,2021,1990,1990,1991,1991,1992,1992,1992,1993,1993,1993,1994,1994,1994,1995,1995,1995,1996,1996,1996,1997,1997,1997,1998,1998,1998,1999,1999)
year <- c("Italy","Netherlands","Netherlands","Sweden","Sweden","UnitedKingdom","UnitedKingdom","Germany","Spain","Spain","Germany","Germany","Germany","Netherlands","Netherlands","UnitedKingdom","UnitedKingdom","Germany","Germany","Belgium","Ireland","Ireland","UnitedKingdom","UnitedKingdom","Belgium","France","France","Germany","Germany","Germany","Portugal","Portugal","Spain","Spain","Italy","Italy","Sweden","Sweden","Germany","Germany","Belgium","Germany","Germany","Germany","Spain","Spain","UnitedKingdom","UnitedKingdom","Spain","Spain","Sweden","Sweden","UnitedKingdom","UnitedKingdom","Germany","Germany","Germany","Italy","Italy","Belgium","Germany","Germany","Germany","Belgium","Germany","Spain","Spain","Germany","Germany","UnitedKingdom","UnitedKingdom","Ireland","Germany","Ireland","UnitedKingdom","UnitedKingdom","Germany","Germany","Germany","Sweden","Sweden","UnitedKingdom","UnitedKingdom","Germany","Germany","France","France","Germany","Germany","Ireland","Ireland","Netherlands","Netherlands","UnitedKingdom","UnitedKingdom","Germany","Germany","Italy","Spain","Germany","Italy","Germany","Germany","Sweden","Sweden","UnitedKingdom","UnitedKingdom","Greece","Greece","Germany","UnitedKingdom","UnitedKingdom","France","France","Germany","Greece","Greece","France","Belgium","Germany","Sweden","Germany","Sweden","Finland","Finland","Italy","Italy","Spain","Spain","Sweden","Sweden","UnitedKingdom","UnitedKingdom","UnitedKingdom","Germany","Germany","Germany","Germany","Germany","Greece","Greece","UnitedKingdom","UnitedKingdom","UnitedKingdom","Germany","Germany","Greece","Greece","France","France","Germany","France","Germany","Germany","Finland","France","Germany","Greece","Portugal","Portugal","Germany","UnitedKingdom","Germany","Germany","Germany","Germany","France","UnitedKingdom","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany","Germany")
country <- c(1,1,1,1,1,1,1,2,4,4,9,11,1,1,1,1,1,4,4,1,1,1,1,1,2,2,2,2,2,1,1,1,1,1,2,2,2,2,3,6,1,1,1,1,1,1,3,3,1,1,1,1,1,1,4,4,4,1,1,2,1,2,2,3,1,1,1,2,2,3,3,1,2,2,3,3,4,4,1,1,1,1,1,2,3,1,1,1,1,1,1,1,1,2,2,1,1,1,1,2,2,1,1,1,1,1,1,2,2,6,1,1,2,2,1,2,2,5,1,4,1,2,3,1,1,1,1,1,1,1,1,1,2,2,3,3,11,1,1,1,1,1,1,2,1,1,1,1,1,1,1,2,2,3,1,1,1,1,1,1,4,3,10,1,1,1,2,3,5,5,4,4,4,16,19,3,7,11,1,1,1,3,2,2,1,3,12,5,5,1,1,1,1,6,6)
number <- c("ban","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","incident","fatalities","incident","fatalities","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","ban","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","ban","incident","fatalities","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","ban","fatalities","incident","fatalities","incident","fatalities","incident","incident","fatalities","incident","fatalities","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","ban","ban","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","ban","incident","fatalities","ban","ban","ban","incident","ban","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","incident","fatalities","ban","incident","fatalities","incident","fatalities","incident","fatalities","ban","ban","incident","fatalities","ban","ban","incident","ban","incident","fatalities","ban","ban","fatalities","ban","incident","fatalities","ban","ban","incident","fatalities","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","ban","incident","fatalities","incident","fatalities","ban","ban","incident","fatalities","incident","fatalities")
type
<- data.frame(year,country,number,type)
PREORTV <- PREORTV[ which(PREORTV$country=='Germany'),]
deRTV
<- ggplot(deRTV, aes(x = year, y = number, fill = type)) +
RTVde geom_col(width = 0.8, position = position_dodge2(3, preserve = "single", padding = 0), color = "black", size = 0.2) +
facet_wrap(~ country,ncol=3) +
scale_fill_manual(values = c("ban"="red", "incident"="lightblue", "fatalities"="black")) +
scale_x_continuous("Year", breaks = seq(1990,2021,1)) +
scale_y_continuous("", breaks = seq(0,20,2)) +
theme_bw() +
theme(strip.text.x = element_text(size = 12, colour = "black", angle = 0)) +
theme(legend.position="bottom", legend.title=element_blank(), legend.text=element_text(size=12),
axis.text.x = element_text(size = 11, angle = 90, vjust = 0.5, hjust=1),
axis.text.y = element_text(size = 11))
RTVde
In Germany, proscriptions have often been used as one response to RWE violence. However, it is, as elsewhere, conspicuous violent incidents that evidently play a crucial role. A series of xenophobic attacks-cum-pogroms in the early 1990s—particularly in Hoyerswerda, Rostock, Solingen, and Mölln—provoked several large demonstrations calling for government action against the violence and eventually resulted in several organisational proscriptions as well as prohibitions against major RWE demonstrations.6
library(ggplot2)
<- c(1990:2021)
Year <- c(128,1483,2277,1609,1489,837,624,790,708,746,998,709,772,759,776,958,1047,980,1042,891,762,755,802,801,990,1408,1600,1054,1088,925,1023,945)
Number <- c(0,0,4,3,1,3,1,1,1,0,2,1,0,1,1,4,1,1,2,3,0,2,6,1,4,2,3,0,0,1,4,1)
Bans <- data.frame(Year, Number, Bans)
banning
ggplot(banning, aes(x = Year)) +
geom_col(aes(y = Bans * 300), fill = "red") +
geom_text(aes(y = Bans * 300, label = round(Bans, 1)), vjust = 1.4, color = "black", size = 5) +
geom_line(aes(y = Number)) +
geom_point(aes(y = Number)) +
theme(text = element_text(size = 15)) +
scale_x_continuous(breaks = seq(1990,2021,1), minor_breaks = seq(1990,2021,1)) +
scale_y_continuous(breaks = seq(0,3000,250)) +
labs(y="Number of far-right violent offences (line)") +
theme_bw() +
theme(axis.text.x = element_text(size = 11, angle = 90, vjust = 0.5, hjust=1),
axis.text.y = element_text(size = 11))
Is proscription used more often where RWE violence occurs more frequently? Figure 6 shows that, yes, it appears that proscriptions in German regions roughly align with RWE homicides, with the greatest clusters of regional proscription decisions coinciding with the higher proportions of fatalities. Botsch, Kopke, and Virchow have already detailed the reliance of Brandenburg—where seven organisations have been proscribed by the regional interior ministry since 1990—authorities on proscription, and verify its beneficial (but not panacean) effects. That only a total of six organisations have been proscribed in Saxony, where there is the highest proportion of RWE fatalities, is curious; one might suspect that here, again, the political considerations of the executive decree mode of proscription are important.
Taken together, the data on PREOs across Europe reveal several patterns: a divide between states where proscriptions are decided by ministries and others where they are decided by courts, as well as states that have not used or even eschew proscription; the spread in recent years of proscription against RWE, epitomised by the UK but also signaled in legislative debates in Denmark, the Netherlands, and Sweden; the transnational character of several recently proscribed organisations, prominently including Identitarians and national branches of the Blood & Honour and Nordic Resistance Movement organisations. These patterns of proscriptions can be explained in part by RWE violence, whereby proscription serves as one response to conspicuous violent incidents. Domestic attacks, not least against political representatives, and even incidents in countries far removed, most especially New Zealand, have pushed the executives of several states to proscribe organisations. Proscription cannot cure all the ills and resolve all the problems of RWE. But it is a tool that many states possess to constrain and disrupt organisational activity that incites hatred, encourages violence, and undermines the constitutional order. Looking closer at the data about PREOs can help to open the lid of the black box concealing proscription decision processes.
This data would not be available without the input of a fantastic team of country experts who participated in data collection: for Austria, Vinicius Bivar and Manès Weisskircher; for Belgium, Ico Maly; for Bulgaria, Rositsa Dzhekova and Asya Metodieva; for Croatia, Maja Gergorić and Ivan Tranfić; for Czechia, Ondřej Kolář and Eva Svatonova; for Denamrk, Richard McNeil-Willson and Anita Nissen; for Estonia, Stefano Braghiroli; for Finland, Lynda Gilby and Tommi Kotonen; for France, Jean-Yves Camus, Nicolas Lebourg, and Franziska Wagner; for Germany, Maik Fielitz, Jana Hitziger, Greta Jasser, Sabine Volk, and Michael C. Zeller; for Greece and for Cyrpus, Andreas Dafnos and Vasiliki Tsagkroni; for Hungary, Katherine Kondor and Balša Lubarda; for Italy, Alessio Scopelliti and Micaela Musacchio Strigone; for Latvia, Valery Engel; for the Netherlands, Sarah de Lange; for Poland, Michael Cole and Justyna Kajta; for Portugal, Vinicius Bivar and Raquel da Silva; for Romania, Roland Clark and Cinpoeş Radu; for Slovakia, Miroslav Mareš and Eva Svatonova; for Slovenia, Miroslav Mareš and Marko Milošev; for Spain, Carmen Aguilera-Carnerero and Bàrbara Molas; for Sweden, Tina Askanius and Patricia Rodi; and for the United Kingdom and for Ireland, William Allchorn, Andreas Dafnos, Callum Downes, and Daniel Jones.
Footnotes
We are indebted to the country experts for Denmark, Anita Nissen and Richard McNeil-Willson, for this observation.↩︎
We thank the country expert for the Netherlands, Sarah de Lange, for this information.↩︎
We thank the country experts for Sweden, Tina Askanius and Patricia Rodi, for this note.↩︎
It is important to note that Golden Dawn has not been proscribed as a “right-wing extremist organisation,” that is on the basis of some ideological criteria, but instead as a “criminal organisation,” on the basis of organised violence and other criminal behaviour by its members. We are indebted to the country experts for Greece, Andreas Dafnos and Vasiliki Tsagkroni, for making this distinction clear.↩︎
Though the first post-war German governments under Konrad Adenauer (1949–1963) implemented denazification in many areas, some implementation was conspicuously hollow. Most notably, several members of Adenauer’s governments had held senior positions in the National Socialist regime, for example: Hans Globke, who was appointed Chief of Staff for the West German Chancellery, had helped draft the racialist Nuremberg Laws and worked closely with Adolf Eichmann to administer parts of the Holocaust; Interior Minister Gerhard Schröder had been a Nazi party member and storm trooper since 1933; the minister for refugees Theodor Oberländer had served in a SS battalion implicated in war crimes in Poland and Ukraine; and Reinhard Gehlen, a leading military intelligence officer in the Nazi regime, became the first president of the German Federal Intelligence Service (Bundesnachtichtendienst).↩︎
In an earlier article in Social Movement Studies, I show how violent anti-fascist counter-mobilisation compelled German state authorities to ban the large, annual neo-Nazi demonstration in Wunsiedel.↩︎