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Article

An Examination of the American Far Right’s Anti-Tax Financial Crimes

Brandon A. Sullivan1,*, Joshua D. Freilich2, and Steven M. Chermak3

Abstract Little attention has been paid to ideologically motivated tax protesters who use frivolous legal arguments as moral or legal justification for committing tax fraud and related financial crimes. These crimes have defrauded private citizens and governments and are associated with violent far-right extremism, negatively impacting public safety and stability. Using data from the U.S. Extremist Financial Crime Database, we provide an exploratory, descriptive analysis of the composition and motivation of financial crime schemes associated with the American far-right extremist anti-tax movement. Our innovative open-source database permits systematic empirical research into con- nections among tax avoidance, anti-tax, and anti-government belief and related criminal behavior, which is necessary for the advancement of scholarship on the causes and consequences of these frauds and the development of sound intervention and prevention policies and practices.

Keywords far-right extremism, tax fraud, ideologically motivated financial crimes, white-collar crime, paper terrorism, sovereign citizen

This study focuses on a sparsely examined problem at the intersection of financial crime and

political and religious extremism: the far-right extremist (FRE) criminal anti-tax movement in the

United States (U.S.).1 Financial crimes receive less attention than other types of crime (e.g., violent

incidents). Specifically, tax evasion and avoidance remain a persistent problem not prevalently

studied in criminology and criminal justice research (Levi, 2010). Research on tax fraud has typi-

cally centered on wealthy individuals and large corporations due to the vast scale and impact of their

crimes (U.S. Government Accountability Office, 2008). However, tax and other financial crimes are

attractive to all areas of society, including FRE with an ideological belief system outside of the

mainstream’s generally accepted political and religious views.

1 Michigan State University, East Lansing, MI, USA 2 Department of Criminal Justice, John Jay College, New York, NY, USA 3 School of Criminal Justice, Michigan State University, East Lansing, MI, USA

*The author is now affiliated to School of Social Sciences, Indiana University Southeast, 4201 Grant Line Road,

034 Crestview Hall, New Albany, IN 47150, USA. Email: [email protected]

Corresponding Author:

Brandon A. Sullivan, Michigan State University, 655 Auditorium Road, Baker Hall, Room 557, East Lansing, MI 48824, USA.

Email: [email protected]

Criminal Justice Review 2019, Vol. 44(4) 492-514 ª 2019 Georgia State University Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0734016819839772 journals.sagepub.com/home/cjr

FRE crimes have resulted in many fatalities, injuries, property damage, and financial losses. FRE,

and most prevalently anti-tax extremists, have committed over 600 financial schemes in the U.S.

from 1990 to 2013 (with over 100 more identified since 2014), 59% (n¼ 359) of which involved tax

refusal and avoidance, resulting in a conservative estimate of over US$1 billion in losses (Sullivan,

Freilich, & Chermak, 2015). Anti-tax proponents utilize various “frivolous arguments,” or alterna-

tive theories of the Constitution and tax law, as a moral or legal justification for not following the

law (Anti-Defamation League [ADL], 2005).2 Many of their crimes are ideologically motivated,-

stemming from a desire to disrupt the U.S. financial system (e.g., tax avoidance, check, and bank

fraud).3 These crimes cause tremendous harm to both private citizens and governments while

supporting violence in some cases, representing an area of growing concern. State police have

reported FRE as a persistent threat to public safety (Carter, Chermak, Carter, & Drew, 2014;

Chermak, Freilich, & Simone, 2010; Freilich, Chermak, & Simone, 2009).

Since 1990, FRE have committed over 210 ideologically motivated homicides claiming close to

300 fatalities (including close to 50 police officers), as being involved in foiled plots that aimed to

attack over 500 specific or general targets (Freilich, Chermak, Gruenewald, Parkin, & Klein, 2018).4

Despite the threat to public safety and stability, nonviolent crimes and their relationship to terrorism

have received less attention. Most research on extremism and terrorism focuses on a small number of

high-profile violent incidents while rarely mentioning financial crimes, material support, terrorism

financing, or preparatory crimes committed by ideologically motivated offenders (Gruenewald,

Freilich, & Chermak, 2009). This is an important omission in the literature, as these non-violent

crimes committed by FRE should not be overlooked. Our study addresses this knowledge gap

through an empirical assessment of financial crime schemes involving FRE tax protesters in the U.S.

We utilize an innovative open-source database to provide an exploratory, descriptive analysis of

the characteristics of crime schemes and offenders associated with the American FRE anti-tax

movement. The U.S. Extremist Financial Crime Database (EFCDB), the Financial Crimes section

of the Extremist Crime Database (ECDB), is the only available data we are aware of on financial

crime schemes committed by political and religious extremists. It consists of rich quantitative and

qualitative data on known criminal cases, allowing for systematic empirical research into connec-

tions among tax avoidance, anti-tax, and anti-government beliefs and behaviors. This is necessary

for the advancement of scholarship on the causes and consequences of these frauds and the devel-

opment of intervention and prevention strategies to curtail them (Braithwaite, 2010; Leighton, 2010;

Levi, 2010).

We first provide an overview of the beliefs and criminal behaviors shaping the FRE anti-tax

movement. We then outline our open-source approach, followed by the results of our descriptive

examination focusing specifically on motivations for engaging in extremist financial crimes. We

conclude with the implications of our study for theory and policy, including areas of future research.

Anti-Tax Belief and Criminal Behavior

Anti-tax extremists (also referred to as tax protesters or tax deniers) are a subsection of FRE

ideologically opposed to taxation who use various frivolous legal arguments to justify their criminal

behaviors. The development of extremist beliefs and behaviors is shaped by many factors. Some are

driven by personal political grievance or victimization, while others are motivated by feelings of

strain and oppression from an external force threatening their values or identity (McCauley &

Moskalenko, 2008, 2011). Extremists often express feelings of grievance or victimization, where

an individual perceives some injustice has been inflicted on them, someone they know, or a larger

identity group. In this view, the individual adopts extremist views or joins an extremist group to gain

a measure of vengeance against their oppressors. Among anti-tax extremists, the oppressor is an

illegitimate government authority that imposes illegal tax and other laws on American citizens. This

Sullivan et al. 493

can be seen in the actions of many anti-tax extremists who feel that the U.S. Internal Revenue

Service (IRS; often represented by an IRS agent) has wronged them or treated them unfairly,

which can manifest itself in more general hostility and potentially lead to actions against the

perceived wrongdoer, such as filing false liens or other legal documents or acting the anger out

with violence. This is consistent with general strain theory, where blocked opportunities, the

imposition of negative stimuli, or the removal of positive stimuli influence the development of

personal grievances that can then lead to criminal behavior (Agnew, 2016). Feelings of victimiza-

tion or grievance can also serve as a catalyst toward engaging with others holding similar views,

further solidifying increasingly extremist beliefs and potentially leading to additional crimes. The

strength of relational influences (particularly family and peers) on criminal behavior is a predo-

minant aspect of social network, social learning, differential association, and social bond theories.

While not everyone who holds extremist beliefs will act on them, social cohesion amplifies these

beliefs and increases the likelihood of individual and collective action (McCauley & Moskalenko,

2014), including both ideologically motivated financial and violent crime.

FRE commit financial crimes in different ways. Some act alone in “lone-wolf”5 schemes or with a

partner (e.g., married couples avoiding taxes), while others collaborate within informal co-offender

networks. Anti-tax offenders may have direct ties with others holding similar ideological beliefs but

could also “self-radicalize” by obtaining information from indirect sources, such as the Internet or

other movement literature (Gill, Lee, Rethemeyer, Horgan, & Asal, 2014; Gruenewald, Chermak, &

Freilich, 2013a). In a survey of state police agencies, 50% responded that anti-tax protesters com-

mitted their crimes alone, as opposed to just over 20% of Christian Identity proponents and 30% of

sovereign citizens (Chermak et al., 2010). This is logical given the nature of tax crimes often

consisting of individual tax avoidance. Lone-wolf offenders, though acting alone, may have ties

to the anti-tax social movement, identifying with their extremist beliefs (Gruenewald et al., 2013a).

Those seemingly acting alone likely have some loose association to the broader movement, where

ideas driving anti-tax ideology are developed, engrained, and sustained (Moskalenko & McCauley,

2011). This promotes an “us” versus “them” mentality with the dehumanization of others to reduce

psychological inhibitions toward extreme ideas (Freilich, Almanzar, & Rivera, 1999; McCauley &

Moskalenko, 2008; Spaaij, 2010). While some join extremist groups and are further radicalized due

to their increased associations with like-minded peers, others may be motivated to act on their own

without joining any formal or informal group (McCauley & Moskalenko, 2008).

Anti-tax beliefs that the tax system and tax laws are illegal and unconstitutional can evolve into

the belief that the entire government is corrupt and illegitimate, which can lead to the adoption of

increasingly extremist ideologies (ADL, 2005). Many tax protesters are also “sovereign citizens”

(sometimes referred to as “freemen”). Proponents of this ideology believe they are either a sovereign

entity not subject to government authority, or a citizen of a fictitious state body, such as a

“sovereign” state republic (e.g. the Republic of Texas).6 The belief that the government holds no

legal authority over them puts sovereign citizens in frequent and persistent conflict with govern-

mental authorities of all levels and jurisdictions, including law enforcement. Sovereign citizens are

frequently involved in violent altercations with law enforcement, posing a persistent threat to public

safety. In a 2013 survey of state and local law enforcement intelligence officers, Carter, Chermak,

Carter, and Drew (2014) found sovereign citizens to be their most serious threat, up from seventh in

a 2006 survey by Freilich, Chermak, and Simone (2009). Although the true number of sovereign

citizens is impossible to know due to their individualistic and secretive nature, some have estimated

their numbers to be in the tens of thousands (ADL, 2012). A common intimidation, retaliation, and

harassment tactic used by sovereign citizens (also referred to as “paper terrorism”) involves filing

frivolous liens and other legal documents against both government officials and private citizens who

they believe have wronged them or their peers (ADL, 2012; Barkun, 2007; Flynn & Gerhardt, 1995;

Pitcavage, 1998, 1999). There is further evidence of an “escalation” in radicalization, where

494 Criminal Justice Review 44(4)

individuals become involved in extremist activity by first engaging in ideologically motivated tax

avoidance or other financial schemes, only to later promote violence as their commitment to

extremist ideology solidifies (Freilich & Chermak, 2009).

While typically driven by ideology, there are a range of motivations for FRE engaging in

financial crimes, from purely ideological based on anti-tax beliefs to the desire for personal profit

(Belli, 2011). Some are indeed ideologically motivated but also take advantage of widespread

distrust of the government, dislike for paying taxes, and ignorance of the law to defraud victims

to commit various types of profit-motivated financial schemes. This suggests that these criminals

can hold FRE beliefs and carry out schemes with either ideological or profit motivations. In addition,

FRE tax protesters often collaborate with others who don’t adhere to their beliefs to carry out

different types of schemes with varying levels of complexity.

The complexity of these anti-tax beliefs and behaviors is the central focus of the current

study. We provide an exploratory, descriptive analysis of the FRE criminal anti-tax movement

utilizing data from the EFCDB, which consists of U.S.-based financial crimes committed by

political and religious extremists. We address the following research question: What is the

composition and motivation of financial crime schemes linked to the American FRE criminal

anti-tax movement? Specifically, we contrast the motivations of extremist ideology and the

desire for financial gain or profit as the driving forces behind these financial crime schemes and

the individuals carrying them out.

Data and Methods

We utilize data from the Financial Crimes section of the U.S. ECDB,7 known also as the EFCDB,

which assembles open-source information on the financial crimes committed by extremists, such as

tax avoidance, bank fraud, and money laundering. The ECDB specifically targets non-violent

financial crimes as part of its inclusion criteria, unlike most American terrorism databases and

definitions that require terrorist acts to use “force or violence” and exclude non-violent financial

crimes. As financial crimes are often difficult to categorize and quantify, we extend prior research by

examining a unique unit of analysis called the “scheme” to capture the complexities of these

offenses. We conceptualize a financial scheme as an “illicit financial operation involving a set of

activities (i.e. techniques) carried out by one or more perpetrators to obtain unlawful gain or other

economic advantage through the use of deliberate deception” (Freilich, Chermak, Belli, Gruene-

wald, & Parkin, 2014, p. 384). Crimes involving distinguishable offenses, techniques, goals, offen-

ders, time periods, and locations are typically treated as distinct schemes. For example, one discrete

scheme involved six tax protesters who sold more than 150 “common law” trusts in a tax avoidance

scheme called the American Asset Protection from 1993 to 1999 in Florida, resulting in more than

US$2 million in lost tax revenue. Individual offenders can have their own distinct roles and engage

in numerous techniques toward carrying out a scheme, such as fund-raising, money laundering,

creating false legal documents, administration, or marketing.

The EFCDB contains all financially related crimes committed by FRE meeting specific inclusion

criteria. Namely, the scheme must involve an investigation leading to an indictment8 in a U.S. court

(of any jurisdiction) for U.S.-based financial crime activities (behavioral criterion, e.g., tax fraud,

money laundering, investment fraud, check fraud, and false financial liens), where at least one of the

offenders adhered to a FRE ideology (attitudinal or belief criterion, e.g., White supremacists,

sovereign citizens, militia/patriot, and general anti-tax). These FRE financial schemes have resulted

in losses to diverse sets of victims, including citizens, businesses, financial markets, and government

institutions. In the U.S. from 1990 to 2013, over 600 financial schemes were committed involving

over 1,345 individual perpetrators, 72% (n¼ 969) of which were extremists and 20% (n¼ 264) non-

extremist collaborators (Sullivan et al., 2015).

Sullivan et al. 495

The current study focuses specifically on anti-tax extremists, a subset of FRE involved in nearly

three fourths (73%, n ¼ 440) of the financial schemes captured in the EFCDB. While all tax

protesters are considered FRE for the purposes of this study, not all FRE are necessary tax protesters.

Due to being centered on tax-related protest and denial, the commonalities among the beliefs held by

tax protesters, and their criminal actions consisting overwhelmingly of tax avoidance and similar

financial schemes, anti-tax extremists are uniquely important to study distinctly from other FRE.

The anti-tax movement consists of both extremists relying solely on frivolous tax arguments and

those who are primarily associated with another FRE ideology (e.g., sovereign citizens, White

supremacists, or militia/patriot groups). All financial schemes (not strictly tax avoidance) involving

anti-tax extremists are included in this study to examine the full scope of their engagement in

financial crime activities.

For this study, we selected all FRE financial schemes in the EFCDB involving tax protesters that

were active at any point from 2002 to 2004. This subset of schemes was chosen for the purposes of

manageable data collection to allow sufficient time for the criminal cases to be processed through

the criminal justice system and the appropriate information to be written and disseminated, identi-

fied through ECDB data collection strategies, fully searched and coded, and evaluated. We selected

multiple years to ensure an adequate initial sample similar to the overall content of the central data

set containing all tax protesters. Based on this inclusion criteria, the initial sample included 167

schemes and 331 non-unique criminal offenders. These are non-unique because individuals involved

in multiple schemes were initially coded separately for each scheme to capture variations in motiva-

tions. To ensure the full scope of co-offenders involved in the same criminal activities was included,

we added any additional financial schemes (regardless of the specific type of crime committed) these

offenders participated in along with any additional offenders involved in those schemes. This

resulted in an additional 48 schemes and 113 non-unique offenders. After removing duplicate

offenders (i.e., those involved in multiple schemes), the final study universe consisted of 215

schemes and 368 unique individual offenders.9

In the ECDB, each crime incident or scheme is treated as an individual case study. Information

sources are identified using over 30 web search engines,10 terrorism databases (e.g., the American

Terrorism Study and the Global Terrorism Database), and government (e.g., Federal Bureau of

Investigation, Department of Justice, congressional testimonies) and watch-group reports (e.g., ADL

and the Southern Poverty Law Center). The resulting sources include media accounts, government

documents, court records, videos, blogs, books, watchdog group reports, movement materials, and

scholarly accounts. This triangulation of multiple data sources overcomes the limitations of single

sources, reducing the chances of bias and increasing reliability and construct validity (Chermak,

Freilich, Parkin, & Lynch, 2012). In addition, we accounted for source reliability by giving more

weight to vetted sources, like court documents, compared to other sources such as personal blogs or

media reports (Sageman, 2004).

For each case study, trained graduate student coders reviewed the open-source materials, deter-

mined whether the ECFDB inclusion criteria were satisfied, and coded data into several unique

databases including a scheme database (i.e., information on the criminal events and activities

themselves) and an offender database (i.e., known offenders indicted for their involvement in the

scheme), which is an innovation extending beyond the majority of efforts focusing solely on a single

unit of analysis. Coded data were initially entered into Microsoft Access, then reviewed and updated

as new information became available to minimize missing data and selectivity bias. Coders first

created a time line and listed the number of schemes and offenders meeting the EFCDB criteria. If a

scheme had multiple offenders, each offender was coded. If one offender met the EFCDB attitudinal

criteria, every additional actor involved in a financial scheme with that offender was also coded. The

EFCDB project manager (lead author) reviewed cases identified by the coders as not meeting the

inclusion criteria to make the final inclusion determination. As multiple research assistants

496 Criminal Justice Review 44(4)

originally coded the data, the lead author reexamined the reliability of the coding and made revisions

for quality and accuracy prior to analysis. By ensuring coding consistency in values across cases,

potential interrater reliability issues were minimized.

We assess numerous scheme and offender characteristics using descriptive statistics. As motiva-

tions are the primary focus of the current study, these variables warrant additional explanation.

Numerous indicators of an extremist connection were identified and documented to demonstrate the

association with an extremist ideology. To do this, specific information about beliefs was mined

from the open-source documents to determine how each offender fit the description of an FRE.

Specifically, personal statements, literature, music, tattoos (e.g., swastika), and FRE group mem-

bership all served as evidence of an extremist belief system. Behaviors are viewed with greater

caution, as we try to avoid inferring beliefs based on actions. However, actions closely following an

established pattern of behavior typical of tax protesters or sovereign citizens could also count as

extremist evidence. In these cases, the lead author closely examined the open-source materials to

determine whether it met the EFCDB inclusion criteria.

Specific pieces of evidence contradicting an extremist association were also recorded to assess

the strength of the connection. Examples include mental illness, a desire for personal financial gain

or profit, or little to no evidence of a direct ideological link for the offender. Profit motive as

contradictory evidence for an individual only applied when the scheme and offender ideology were

intrinsically tied together. In many cases, the only evidence of an extremist association was directly

tied to the scheme in that the extremist beliefs and arguments were used to carry out the scheme. If

an individual used sovereign citizen or anti-tax ideas or tactics in the commission of the scheme but

evidence also existed that the individual used them to generate substantial personal wealth, the profit

motive undermined the extremist association and was therefore coded as contradictory evidence. In

other cases, the ideological connection of the offender was strong, but the scheme motive was

nonideological (e.g., a White supremacist committing check fraud solely for personal profit), so

the profit motive was not coded as contradictory evidence because engaging in a scheme for profit

does not undermine the ideological association of the offender. For many offenders, no evidence of a

direct extremist link could be established despite the individual being involved in a scheme with

FRE. In these cases, the offender was coded as a nonextremist. This is important because an

ideological connection was not assumed and required direct evidence to be coded as an extremist.

We differentiate scheme and offender motivations as two separate units of analysis. The scheme

motivation is the overall goal or purpose of the financial crime scheme (ideology, profit, or a

combination of the two). While there are numerous other possible goals, our focus for this study

centers on the contrast between ideology and profit motivations. A scheme is considered primarily

ideologically motivated if it is carried out to further a FRE belief system or to finance the activities

of an FRE group. Schemes related to a FRE goal but not primarily driven by the desire to further its

extremist belief system are treated as a hybrid or middle category between ideology and profit. Other

schemes involved at least one FRE but were driven by nonideological goals, primarily profit.

Individual offender motivations (ideological, profit, mixed ideological and profit, or another goal)

were differentiated from the goal of the overall scheme operation.

To distinguish between schemes and offenders with strong extremist connections and those with

relatively weak connections, we utilize a scale to measure the strength of association to account for

evidence supporting and contradicting an extremist association (Table 1).11 This scale assesses the

intensity of the affiliation to an extremist ideology using multiple pieces of open-source information.

We also created a similar scale to assess the extent of profit motivation, where evidence for profit

motivation is contrasted with evidence contradicting profit motivation. Both units of analysis were

independently assessed for evidence of ideological and profit motivation, receiving a score from 0

(low) to 4 (high). Some were high on one scale and low on the other, while others were high on both

scales. Schemes and offenders found to have mixed ideology and profit motives may be high in both

Sullivan et al. 497

T a b

le 1 .

St re

n gt

h o f A

ss o ci

at io

n .

V al

u e

Id eo

lo gy

P ro

fit

C at

eg o ry

C ri

te ri

a

C at

eg o ry

C ri

te ri

a Sc

h em

e O

ff en

d er

Sc h em

e O

ff en

d er

4 U

n d is

p u te

d es

ta b lis

h ed

id eo

lo gi

ca l

m o ti ve

to fu

rt h er

FR E

go al

s

U n d is

p u te

d es

ta b lis

h ed

p re

se n t

o r

p as

t ad

h er

en ce

to FR

E id

eo lo

gy

� M

u lt ip

le (t

w o

o r

m o re

) FR

E in

d ic

at o rs

� N

o ev

id en

ce co

n tr

ar y

to FR

E as

so ci

at io

n

U n d is

p u te

d es

ta b lis

h ed

p ro

fit m

o ti ve

, n o

ap p ar

en t

id eo

lo gi

ca l

m o ti ve

U n d is

p u te

d es

ta b lis

h ed

p ro

fit m

o ti ve

, n o

ap p ar

en t

co n n ec

ti o n

to FR

E id

eo lo

gy

� M

u lt ip

le (t

w o

o r

m o re

) p ro

fit in

d ic

at o rs

� N

o ev

id en

ce fo

u n d

co n tr

ar y

to es

ta b lis

h an

o th

er m

o ti ve

(i n d ic

at o rs

o f FR

E id

eo lo

gy , et

c. )

3 C

le ar

es ta

b lis

h ed

id eo

lo gi

ca l

m o ti ve

to fu

rt h er

FR E

go al

s

C le

ar es

ta b lis

h ed

p re

se n t

o r

p as

t ad

h er

en ce

to FR

E id

eo lo

gy

� O

n ly

si n gl

e FR

E in

d ic

at o r

� N

o ev

id en

ce co

n tr

ar y

to FR

E as

so ci

at io

n

C le

ar es

ta b lis

h ed

p ro

fit m

o ti ve

C le

ar es

ta b lis

h ed

p ro

fit m

o ti ve

� O

n ly

si n gl

e p ro

fit in

d ic

at o r

� N

o ev

id en

ce co

n tr

ar y

to es

ta b lis

h an

o th

er m

o ti ve

(i n d ic

at o rs

o f FR

E id

eo lo

gy , et

c. )

2 D

is p u te

d es

ta b lis

h ed

id eo

lo gi

ca l

m o ti ve

to fu

rt h er

FR E

go al

s

D is

p u te

d p re

se n t

o r

p as

t ad

h er

en ce

to FR

E id

eo lo

gy

� M

u lt ip

le (t

w o

o r

m o re

) FR

E in

d ic

at o rs

� E vi

d en

ce co

n tr

ar y

to FR

E as

so ci

at io

n

D is

p u te

d es

ta b lis

h ed

p ro

fit m

o ti ve

,e vi

d en

ce o f o th

er p o te

n ti al

m o ti ve

s (e

.g .,

id eo

lo gy

)

D is

p u te

d p ro

fit m

o ti ve

, ev

id en

ce o f o th

er p o te

n ti al

m o ti ve

s (e

.g .,

FR E

id eo

lo gy

, m

en ta

l ill

n es

s)

� M

u lt ip

le (t

w o

o r

m o re

) p ro

fit in

d ic

at o rs

� E vi

d en

ce co

n tr

ar y

to p ro

fit m

o ti ve

(i n d ic

at o rs

o f FR

E id

eo lo

gy , et

c. )

1 D

is p u te

d es

ta b lis

h ed

id eo

lo gi

ca l

m o ti ve

to fu

rt h er

FR E

go al

s

D is

p u te

d es

ta b lis

h ed

p re

se n t

o r

p as

t ad

h er

en ce

to FR

E id

eo lo

gy

� O

n ly

si n gl

e FR

E in

d ic

at o r

� E vi

d en

ce co

n tr

ar y

to FR

E as

so ci

at io

n

D is

p u te

d p ro

fit m

o ti ve

, es

ta b lis

h ed

ev id

en ce

o f

o th

er m

o ti ve

s (e

.g .,

FR E

id eo

lo gy

)

D is

p u te

d p ro

fit m

o ti ve

, es

ta b lis

h ed

ev id

en ce

o fo

th er

m o ti ve

s (e

.g .,

FR E

id eo

lo gy

, m

en ta

l ill

n es

s)

� O

n ly

si n gl

e p ro

fit m

o ti ve

in d ic

at o r

� E vi

d en

ce co

n tr

ar y

to p ro

fit m

o ti ve

(i n d ic

at o rs

o f FR

E id

eo lo

gy , et

c. )

0 N

o ap

p ar

en t

id eo

lo gi

ca l

m o ti ve

N o

es ta

b lis

h ed

p re

se n t

o r

p as

t ad

h er

en ce

to FR

E id

eo lo

gy

� N

o FR

E in

d ic

at o rs

� E vi

d en

ce co

n tr

ar y

to FR

E as

so ci

at io

n

N o

es ta

b lis

h ed

p ro

fit m

o ti ve

N o

es ta

b lis

h ed

p ro

fit m

o ti ve

� N

o p ro

fit in

d ic

at o r

� E vi

d en

ce co

n tr

ar y

to p ro

fit m

o ti ve

(i n d ic

at o rs

o f FR

E id

eo lo

gy , et

c. )

498

ideology and profit, but not as high as those where the available evidence points to either motive as

the main driving force. There were also cases where offenders were high on both the ideology and

profit scales, as their scheme activities did not in any way contradict their ideological connection.12

One of the limitations to assessing motivations is the potential for incomplete or inaccurate

portrayals in the open-source information. Parkin (2012) identified several ways this could occur.

First, an extremist link could either go undiscovered or not reported in the source document. Second,

an extremist connection could be portrayed inaccurately or incompletely, making the ideological

link appear to be different than it is. Third, individuals could be portrayed as having an extremist

connection when one does not exist. This could be due to assumptions made by the source author

based on the individual’s behavior or relationships with others holding extremist views. These

potential inaccuracies do not discount the value of data gleamed from open sources like the ECDB

but rather provide context for how the data should be interpreted (Parkin, 2012).

Findings

Financial Schemes

Again, we identified 215 financial crime schemes committed by 368 unique individual criminal

offenders meeting our inclusion criteria. We first examined scheme-level characteristics (Table 2)

including type, size, and length.

Type. Not surprisingly, tax avoidance (n ¼ 176, 82%) was the most prominent scheme type. The

composition and content of these tax avoidance schemes varied widely, including failing to file

income tax returns, submitting false tax returns, sending false documentation to officials to obstruct

or impede the collection of taxes, and the sale of anti-tax packages based on anti-tax and sovereign

citizen arguments, where those looking to save money on taxes by taking advantage of the scam

Table 2. Scheme Characteristics.

Scheme Variables

Total (N ¼ 215) Lone-Wolf (N ¼ 142) Multi-Offender (N ¼ 73)

Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD)

Size Offenders 1–27 2.08 (2.81) — — 2–27 4.18 (4.09) Extremist offenders 1–11 1.57 (1.31) — — 1–11 2.69 (1.79) Non-Extremist offenders 0–19 0.50 (2.00) — — 0–19 1.48 (3.23)

Length 1–34 7.28 (5.03) 1–26 6.89 (4.88) 1–34 8.03 (5.27)

N % N % N %

Type 215 100.00 142 100.00 73 100.00 Tax avoidance 176 81.86 114 80.28 62 84.93 False lien 9 4.19 8 5.63 1 1.37 Check fraud 9 4.19 7 4.93 2 2.74 Investment 8 3.72 4 2.82 4 5.48 Banking 3 1.40 2 1.41 1 1.37 Other 10 4.65 7 4.93 3 4.11

Motive 212 100.00 140 100.00 72 100.00 Ideology 130 61.32 93 66.43 37 51.39 Mixed 71 33.49 38 27.14 33 45.83 Profit 11 5.19 9 6.43 2 2.78

Sullivan et al. 499

were charged extravagant fees and provided fake documentation, instructions on how to file false tax

documents, and fake financial instruments to satisfy existing debts. Additional scheme types

included false liens and other frauds (e.g., check, banking, and investment fraud). Nine schemes

(4%), all but one committed by a lone offender, involved filing of frivolous liens and other legal

documents against public officials or private citizens (also known as “paper terrorism”). These false

liens typically claimed billions of dollars in liabilities and were filed against government officials in

retaliation for criminal or civil proceedings brought against them or their peers with the goal of

intimidation and causing financial harm. Check fraud schemes (n ¼ 9, 4%) typically consisted of

fictitious, often self-manufactured2 checks, money orders, or other similar financial instruments,

including those utilized by proponents of the “redemption” or “straw man” theory such as a “sight

draft” or “bill of exchange.” Investment schemes (n¼ 9, 4%) included pyramid and Ponzi frauds and

the use of fake securities instruments. Many revolved around debt elimination, where the victims

were either sold access to nonexistent secret government accounts or promised part of the proceeds

from phony lawsuits against the government under the guise that the money could be used to satisfy

their debts. One popular version involved the offenders declaring themselves to be executors of a

settlement that declared the Federal Reserve bankrupt, promising those who paid the filing fee

(typically US$300) would gain access to millions of dollars in payouts. The remaining schemes

involved banking frauds (e.g., mortgage and credit card fraud), embezzlement, and money

laundering.

Size. Nearly two thirds (66%) of the 215 FRE financial schemes were committed by a lone-wolf

(single individual) offender. This does not mean these offenders did not engage in criminal

activity with others, as schemes often involved unindicted co-conspirators and many lone

offenders were involved in additional schemes, some of which involved co-offenders. The

remaining schemes involved multiple offenders. Many were two individuals working together,

often married or cohabiting couples (e.g., working jointly to avoid taxes, often by failing to file

a return or filing false paperwork), friends, business partners, or other associates. While an

average of approximately two offenders engaged in each scheme, the large number of lone-wolf

schemes heavily skewed this value toward 1. When accounting only for the 73 multi-offender

schemes, the average number of offenders doubled with greater variability between schemes

(M ¼ 4.18, SD ¼ 4.09). A small number of schemes were disproportionately perpetrated by

non-extremist collaborators (only three involved more than 10, while 10 had only 1). These

multi-offender schemes involved an average of 2.69 extremist and 1.48 non-extremist offen-

ders. The largest scheme involved 27 offenders.

Length. The length of these financial schemes varied widely.13 Schemes lasted from less than 1

(rounded to one) to 34 years with an average length of 7.28 years (SD ¼ 5.03). Lone-wolf schemes

(M ¼ 6.89, SD ¼ 4.88) were 1.14 years shorter on average than multi-offender schemes (M ¼ 8.03,

SD ¼ 5.27), although the difference was not statistically significant, independent t test: t(213) ¼ 1.568, p ¼ .118. The number of active schemes per year (Figure 1) followed a clear trajectory,

increasing rapidly throughout the 1990s, peaking around 2002, then gradually declining in the late

2000s to roughly the same numbers as the early 1990s.14 This pattern varied little between lone-wolf

and multi-offender schemes.

Criminal Offenders

We turn next to the characteristics of individual criminal offenders, including demographics (gen-

der, race, age, and residence) and extremist affiliation (Table 3).

500 Criminal Justice Review 44(4)

Demographics. Offenders were generally middle-aged, White males residing disproportionately in

the Southern region of the U.S., albeit with several notable distinctions. First, while over two thirds

were male (n ¼ 287, 78%), there were a substantial number of female offenders (n ¼ 81, 22%).

0

20

40

60

80

100

120

140

160

Total Lone Wolf Multi-Offender

Figure 1. Annual active far-right extremist anti-tax financial crime schemes (1990–2010).

Table 3. Offender Characteristics.

Offender Variables

Total (N ¼ 368) Extremist (N ¼ 279) Non-Extremist (N ¼ 89)

Min–Max Mean (SD) Min–Max Mean (SD) Min–Max Mean (SD)

Age (at start) 19–72 (n ¼ 437) 45.34 (9.95) 19–68 (n ¼ 274) 45.94 (9.67) 20–61 (n ¼ 88) 40.85 (10.14) Age (at end) 22–78 (n ¼ 440) 51.59 (9.77) 22–76 (n ¼ 276) 52.48 (9.60) 28–67 (n ¼ 88) 47.83 (10.10)

N % N % N %

Sex 368 100.00 279 100.00 89 100.00 Male 287 77.99 223 79.93 64 71.91 Female 81 22.01 56 20.07 25 28.09

Race 327 100.00 259 100.00 68 100.00 White 309 94.50 244 94.21 65 95.59 Black 13 3.98 11 4.25 2 2.94 Other 5 1.53 4 1.54 1 1.47

Region 366 100.00 277 100.00 89 100.00 South 152 41.53 122 44.04 30 33.71 West 83 22.68 65 23.47 18 20.22 Northeast 81 22.13 52 18.77 29 32.58 Midwest 41 11.20 29 10.47 12 13.48 Other 9 2.46 9 3.25 0 0.00

Motive 445 100.00 350 100.00 95 100.00 Ideological 225 50.56 225 64.29 — — Mixed 89 20.00 89 25.43 — — Profit 107 24.04 33 9.43 74 77.89 Other/

unknown 24 5.40 3 0.86 21 22.11

Sullivan et al. 501

Second, race was overwhelmingly White (n ¼ 309, 95%), with only 18 non-White offenders (13

Black, 4 Asian, and 1 Native American).15 Third, there was a wide range in offender age.16 The

youngest offenders were 19 (at scheme commencement) and 22 (at scheme desistance) years old

while the oldest were 72 (at commencement) and 78 (at desistance), while the mean ages were 45

and 52 (commencement and desistance, respectively). Non-extremist offenders on average were

roughly 5 years younger than extremists: independent t test: t(360) ¼ �4.243, p ¼ .000; extre-

mists: M ¼ 45.938, SD ¼ 9.667, n ¼ 274; and nonextremists: M ¼ 40.852, SD ¼ 10.141, n ¼ 88.

Fourth, offenders disproportionately resided in the Southern region of the U.S. (n ¼ 152, 42%),

while the fewest came from the Midwest region (n ¼ 41, 11%). The Northeast region had a lower

proportion of extremist offenders compared to other regions (64–78%, w2 ¼ 6.843, p ¼ .009),

while there is some evidence suggesting the Southern region may have a greater proportion (80% to 72%, w2 ¼ 3.466, p ¼ .063). Virtually every state was represented, excluding only Alaska,

Delaware, Kansas, Kentucky, Maryland, Missouri, Vermont, and West Virginia. The most pre-

valent states were Florida (n ¼ 52, 14%), California (n ¼ 32, 9%), Ohio (n ¼ 24, 7%), and

Washington (n ¼ 20, 6%).

Extremist affiliation. Of the 368 offenders, 279 (76%) were identifiable FRE while 89 (24%) were non-

extremist collaborators. Not surprisingly, most held an anti-tax ideology (n¼ 140, 38%) subscribing

to anti-tax beliefs, tactics, and methods but not exhibiting characteristics of sovereign citizens,

White supremacists, or patriot/militia members. Nearly the same number were sovereign citizens

(n ¼ 126, 34%) with the major difference being the reliance on arguments or tactics expressing

sovereignty from the government or citizenship in a nonexistent entity, such as a state republic. The

remaining extremists were affiliated with patriot/militia groups (n ¼ 12, 3%) except for a single

White supremacist, although this individual also adhered to elements of sovereign citizen and

patriot/militia philosophies.

The other 24% (n ¼ 89) of offenders did not exhibit any identifiable expression of extremist

ideology. Non-extremist collaborators seemingly engaged in these schemes primarily for financial

gain and often included individuals with specialized expertise (e.g., tax preparers, lawyers, accoun-

tants, financial planners, office workers, salespersons, and businesspersons) who provided profes-

sional services to further the scheme (e.g., preparing false tax returns, financial instruments, and

legal documents). In other cases, individuals joined the scheme as a financial opportunity after being

introduced to it by family members, friends, or associates. It is important to reiterate that many of

these individuals could also hold FRE attitudes and beliefs, but no evidence was found in the open-

source information.

Motivations for Engaging in Extremist Financial Crimes

We closely examined motivations for engaging in FRE financial crimes. Scheme motivations varied,

but the majority were primarily based on a political or religious extremist ideological belief system

(n¼ 130, 61%) as opposed to profit (n¼ 11, 5%), while one third (n¼ 71, 33%) were motivated by a

combination ideology and profit. Further evidence of this was found in the strength of Ideology and

Profit Association Scales (Table 4), as these schemes had high ideology strength (M ¼ 2.77) and

low-profit strength (M ¼ 0.55). This is largely due to the number of schemes with no evidence

contradicting the ideological association (44%, “4” ideology score) and without any evidence for

profit association as a contributing factor (63%, “0” profit score). At the reverse of the scale, only

two schemes had multiple pieces of profit evidence with no contradictory evidence (“4” profit

score), while the remaining profit-motivated schemes had only a single piece of profit evidence

(“3” profit score). Meanwhile, all 11 profit-motivated schemes had no evidence of ideological

motivation (“0” ideology score).17

502 Criminal Justice Review 44(4)

Motivations differed between lone-wolf and multi-offender schemes and by scheme type. Multi-

offender schemes were more likely than lone-wolf schemes to be motivated by a combination of

ideology and profit (47% to 27%, w2 ¼ 8.097, p ¼ .004) with a “2” score for both ideology (w2 ¼ 5.661, p ¼ .017) and profit (w2 ¼ 1.715, p ¼ .001). Mixed motives for multi-offender schemes is a

logical finding, given the varying contributing influences on a multi-offender operation from dif-

ferent individuals, complicating the overall goal or purpose of the scheme and increasing the like-

lihood of finding evidence for both motivations. While multi-offender schemes were less likely to be

motivated by ideology alone (51–66%, w2 ¼ 5.001, p ¼ .025), there were no differences found

between lone-wolf and multi-offender schemes in terms of pure profit motivation (w2 ¼ 1.333, p ¼ .248) or ideology and profit strength of association scores.18

Motivations also differed by scheme type. Namely, tax avoidance schemes were more likely than

other types of schemes to be motivated by ideology (64% to 46%, w2¼ 4.286, p¼ .038) with higher

ideology strength of association scores and less likely to be motivated by profit (2–21%, w2 ¼ 24.763, p ¼ .000) with lower profit scores.19 In contrast, investment schemes were less likely to

be motivated by ideology than other schemes (13–63%, w2 ¼ 8.232, p ¼ .004) and more likely to be

motivated by profit (38% to 4%, w2 ¼ 17.746, p ¼ .000).20 No differences were found among other

scheme types.

Further nuances were found among individual offender motivations.21 Half (n ¼ 225) were

motivated by ideology, nearly one fourth (n ¼ 107, 24%) by profit, and 20% (n ¼ 89) by mixed

motives. Individual ideology (M ¼ 2.37) and profit motivations (M ¼ 1.03) were more moderate

compared to higher scheme ideology (M ¼ 2.77) and lower scheme profit motivations (M ¼ 0.55).

This largely reflects the number of non-extremist collaborators who, unsurprisingly, had much

higher profit motivation scores than extremists (non-extremist: M ¼ 2.92; extremist: M ¼ 0.57)

Table 4. Scheme and Offender Strength of Ideology and Profit Association.

Ideology Profit

Scheme Total Lone-Wolf Multi-Offender Total Lone-Wolf Multi-Offender

Mean (SD) 2.77 (1.29) 2.81 (1.30) 2.70 (1.28) 0.55 (0.87) 0.48 (0.86) 0.69 (0.88)

Value N % N % N % N % N % N %

0 11 5.16 9 5.16 2 2.74 134 63.21 96 68.57 38 52.78 1 32 15.02 19 15.02 13 17.81 52 24.53 31 22.14 21 29.17 2 45 21.13 23 21.13 22 30.14 15 7.08 4 2.86 11 15.28 3 32 15.02 28 15.02 4 5.48 9 4.25 8 5.71 1 1.39 4 93 43.66 61 43.66 32 43.84 2 0.94 1 0.71 1 1.39 Total 213 100.00 140 100.00 73 100.00 212 100.00 140 100.00 72 100.00

Offender Total Extremist Non-Extremist Total Extremist Non-Extremist

Mean (SD) 2.37 (1.56) 2.95 (1.15) — 1.03 (1.29) 0.57 (0.83) 2.92 (1.16)

Value N % N % N % N % N % N %

0 85 19.59 0 0.00 85 100.00 223 51.62 213 61.21 10 11.90 1 49 11.29 49 14.04 — — 82 18.98 82 23.56 — — 2 92 21.20 92 26.36 — — 46 10.65 46 13.22 — — 3 35 8.06 35 10.03 — — 55 12.73 4 1.15 51 60.71 4 173 39.86 173 49.57 — — 26 6.02 3 0.86 23 27.38 Total 434 100.00 349 100.00 85 100.00 432 100.00 348 100.00 84 100.00

Sullivan et al. 503

and accounted for most of the profit-motivated offenders (n ¼ 74, 69%).22 The remaining 31% (n ¼ 33) were FRE who primarily engaged in financial schemes due to a desire for personal profit instead

of their ideology, although many also engaged in other additional schemes with ideological motives.

While only 9% (n¼ 25) of extremists compared to 78% (n¼ 69) of non-extremists were motived by

profit, it is still a noteworthy number.23

Discussion and Implications

Our study revealed a general description of financial crime schemes linked to the American FRE

anti-tax movement as long-term, lone-wolf, ideologically motivated tax avoidance schemes (using

frivolous anti-tax arguments) committed by middle-aged, White, males residing primarily in the

Southern region of the U.S. This was not necessarily surprising, given the typical FRE profile.

However, there are many caveats to this somewhat broad, overly simplistic generalization. Similar

to extremist violence incidents, we found variation among types of anti-tax offending, when and

where the crimes occurred, who carried them out, and the motivations driving them. Individuals

from all corners of society were involved in these crimes, including tax preparers, accountants,

lawyers, bank executives, medical professionals, farmers, and law enforcement officers. There have

also been cases of individuals with differing ideologies working together to engage in financial

crimes, such as the Black nationalists promoting slavery reparations fraud schemes working with

White sovereign citizens to commit tax avoidance and false lien schemes. This speaks to the

extensiveness of the problem and the dangers of diffusion. The next steps for research in this area

are to account for these variations by identifying theories explaining the causes of these crimes and

policies, practices, and strategies to prevent them.

One third of the financial crimes involving anti-tax extremists were committed by multiple

perpetrators and more likely to be profit-oriented business opportunities due in large part to the

extensive involvement of non-extremist collaborators and the unique roles and skills necessary to

pull off more expansive and intricate criminal operations. These schemes may be more visible and

therefore come under greater scrutiny from law enforcement. They could also lead directly or

indirectly to those engaged in their own lone-wolf schemes based on information or advice received

from others they are affiliated with. Targeting these network connections of individuals involved in

FRE financial crimes can play a key role in limiting the spread of anti-tax behaviors.

The remaining two thirds of the crimes were committed by lone wolves (individuals acting

alone). These mostly involved ideologically motivated tax avoidance, though several were moti-

vated instead by profit or a combination of the two. These schemes generally did not require a great

amount of specialized expertise, knowledge, or skill to carry out beyond than the anti-tax and

sovereign citizen arguments supporting them. Anyone with access to basic information (easily

obtained online or through anti-tax seminars regularly held across the U.S.) could file a false return

and stop paying taxes, use a fake check, or file a false lien. The strategies used to address larger,

more visible anti-tax crime schemes may not be as effective with these lone-wolf schemes. There-

fore, interventions not relying on formal criminal justice tactics are vital to preventing these crimes.

These strategies could rely on the situational crime prevention perspective that not only includes

interventions to discourage or prevent illegal behavior but also encompasses strategies to encourage

compliance with the law and proactive legal actions (Belli & Freilich, 2009). Soft crime prevention

strategies such as those proposed by Belli and Freilich (2009) are aimed at reducing the overall

prominence and acceptance of tax avoidance, including: (1) neutralization of negative influences on

criminal behavior, (2) introduction of positive role models to counter the lure of anti-tax sentiment,

and (3) incentivizing compliance. Unique polices for countering anti-tax and antigovernment beliefs

and attitudes on a wide scale are a key component to preventing these financial crimes and warrant

further attention.

504 Criminal Justice Review 44(4)

The effectiveness of responses to anti-tax financial crimes also depends on the motivations

behind them. While we focused extensively on the contrast between ideological and profit motives,

other motivations did not receive the same attention. The ideological association measurement has

been carefully established and is useful for distinguishing between those with strong and weak

connections to extremist ideology based on identifiable FRE indicators in open-source records.

While a Profit Motivation Scale was developed for this study, further refinement will be necessary

going forward. This includes an interesting problem not addressed in this study related to the

inherent profit motive involved in many anti-tax arguments. While tax avoidance schemes present

the appearance of ideological motivation without direct evidence of profit, they may in fact be

driven by profit. In other words, is the act of tax avoidance an indication of profit motive due to the

resulting personal financial benefit? These situations were not included as evidence of profit motive

for the purposes of this study; otherwise, all ideologically motivated actors would have been found

to be a mix of ideology and profit. Further research into these complexities is certainly warranted.

Theorizing about motivations behind FRE anti-tax crimes, including the spread of anti-tax beliefs

and behaviors, will be important going forward. Examining how these ideas develop and diffuse

widely across time and space is important for understanding how anti-tax ideologies function.

Applying diffusion of innovation theory (Rogers, 2003) could provide interesting insights into

tracking the adoption of anti-tax behaviors in different contexts, including the role of the Internet

in spreading and sustaining these ideas. An important question is the extent to which online exposure

to anti-tax ideas can provoke anti-tax belief or behavior in relation to the contributing factors of

ideological predisposition, peer influences, and catalyst events (e.g., financial difficulty, tax-related

actions taken against the individual). This speaks to the chicken-and-egg problem: Do individuals

become radicalized through FRE propaganda (e.g., anti-tax literature) they happen to come across

online or do individuals who already hold anti-government views or who wish to avoid paying taxes

seek out those promoting anti-tax arguments to justify their preexisting beliefs and behavior? The

answer depends on individual, situational, and relational considerations. This study dealt with anti-

tax beliefs and behaviors but did not speak to the circumstances surrounding their adoption. Life

events or circumstances (turning points) outlined in life-course theory (see Hamm, 2011), or the

removal of positive stimuli in general strain theory (see Agnew, 2016) could offer insight into the

origin of these anti-tax beliefs and behaviors. While it appears that the adoption of ideology led to

financial crime behaviors, the inverse may be true in many cases, where the internal desire for

personal fulfillment, financial gain, or retribution-led individuals to seek out anti-tax extremist belief

system to justify those desires. Different theories could potentially explain the causal order, such as

social learning theory (see Akins & Winfree, 2016) focusing on radicalization into anti-tax beliefs

and behaviors based on observations of role models and interactions with others who show them how

to carry out financial schemes using similar techniques. Others engaged in tax avoidance for

personal gain could adopt various neutralization techniques (including an anti-tax ideology) to

justify their behavior.

The overwhelming number of ideologically motivated lone offenders involved in these financial

schemes fits with theories for how individuals come to embrace extremist beliefs and behaviors.

Many exhibited both personal and political grievances and externalized the government as the

enemy, which is consistent with several of McCauley and Moskalenko’s (2008, 2011) mechanisms

of radicalization. The role of societal forces in shaping financial crime schemes among anti-tax

extremists should also be examined in further depth. Several other theories could explain radicaliza-

tion among lone-wolf financial offenders, including mass society (consensus) and resource mobi-

lization (conflict) theories (see Freilich, 2003; Freilich & Pridemore, 2005), which focus on societal

shifts leading to the externalization of blame for difficult circumstances toward an outside reference

group and the breakdown of existing social structures, increasing the likelihood of the adoption of

extremist beliefs. This study does not account for these societal conditions, but the overwhelming

Sullivan et al. 505

number of disconnected lone wolves with similar offending patterns suggests that social movement

theories could further explain the prevalence of anti-tax beliefs and behaviors.

Another important area of research is to compare FRE financial crime to other types of crimes

associated with other extremist ideologies. In contrast to FRE that have engaged mostly in financial

crimes centered on an anti-government ideology, jihadi extremists have committed mostly monetary

and material support crimes such as providing money or other resources, supplies, training, or

personnel to foreign terrorist organizations or causes (Sullivan, Freilich, & Chermak, 2016). Mean-

while, we have not to date identified any financial schemes associated with far-left ideologies (e.g.

environmental and animal rights extremists). While FRE financial crimes mostly impact individuals,

businesses, and governments in the U.S., jihadi financial crimes contribute to overseas extremist

activities including the support of terrorist organizations and the furtherance of violent plots. In

addition, we have identified a few cases of FRE and jihadi extremist collaborations in violent and

financial offending, which warrants further attention. Future research should investigate whether

recruitment processes and radicalization mechanisms are the same across these movements and the

extent to which financial crime activities impact future violent extremism.

Further, it is notable that lone-wolf financial crime offending coincides with findings from

previous studies of a decline in lone-wolf violent offending over the course of the 2000s after the

extraordinarily high levels of the 1990s (Gruenewald, Chermak, & Freilich, 2013b; Spaaij, 2010).

Using RAND Memorial Institute for the Prevention of Terrorism (MIPT) incident data, Spaaij

(2010) found that lone-wolf attacks increased sharply starting in the 1970s, peaked in the 1990s,

and declined in the 2000s but to levels still above those of the 1980s. Using ECDB data, Gruenewald,

Chermak, and Freilich (2013b) found further support for this decrease, noting a sharp downward

trend in FRE lone-wolf homicides after 2001 from the highs of the 1990s. This sharply contrasts

claims often made of consistently rising levels of lone-wolf terrorism by policy makers and the news

media. However, the large number of foiled and failed violent plots by FRE is not often considered

in the same threat evaluations as homicides and could potentially offset the decrease in violent

incidents (Dahl, 2011; Gruenewald et al., 2013b). In addition, FRE financial crime schemes are

likely to be much more extensive than has been accounted for, as the number of active schemes will

increase as future indictments reflect criminal activity that occurred throughout this time period,

particularly for the later years.24 Official records of financial crimes are also highly dependent on the

will to prioritize criminal cases against these offenders, which fluctuates greatly over time.

The concentration of FRE anti-tax schemes in the Southern region of the U.S. is notable and

consistent with prior research on FRE ideologically motivated homicides. Namely, Florida and

Texas have been among the states with the highest number of ideologically motivated homicides

and violent plots (see Freilich et al., 2018) in addition to financial crime schemes. FRE anti-tax

financial crimes have also been prevalent in Arizona. However, California, Washington, Illinois,

Ohio, Pennsylvania, Colorado, Oregon, and Massachusetts have also seen a large number of these

crimes, which does not indicate an obvious pattern. The fact that many of these states are also the

most populous in the U.S. suggests that these findings are at least in part a function of state

population. While spatial variation of FRE violence has recently received increased empirical

attention (see Chermak & Gruenewald, 2015; Fitzpatrick, Gruenewald, Smith, & Roberts, 2016;

Freilich, Adamczyk, Chermak, Boyd, & Parkin, 2015), FRE financial crime has not yet been

addressed and will be an important area for future research.

A final note speaks to the difficulty in studying FRE financial crime. Conceptually, these unique

crimes are difficult to situate in the existing literature, presenting challenges for operationalizing key

constructs. As established approaches are limited, the EFCDB is currently the only available data-

base we are aware of for studying these crimes. This rich database provides the unique opportunity to

answer numerous questions and conduct various types of studies that were not previously possible.

506 Criminal Justice Review 44(4)

That said, studies examining the anti-tax movement using non-archival methods, such as interviews,

observations, or surveys, will be important and fruitful avenues of future research.

Conclusion

Financial crimes involving FRE deserve more attention from scholars, policy makers, and practi-

tioners. Despite the large number of FRE involved in ideologically motivated tax avoidance as a

form of government protest, false legal documents used to obstruct and harm government officials

and private citizens, and other harmful financial crimes, far greater resources have been devoted

toward international extremist groups than far-right domestic extremism or the financial and orga-

nizational aspects of extremism. In addition to financial harms, many FRE financial schemes are

associated with violent incidents including standoffs with police, retaliatory acts of violence, and

weapons stockpiling. Some tax protesters have been found to escalate from tax avoidance to vio-

lence against police officers, other government officials, and the public. Therefore, exclusively

focusing on extremist violence is artificially limiting. Our study illustrates the importance of con-

ducting systematic analyses of these financial schemes and points to the need for a more compre-

hensive focus on broader criminal networks consisting of both extremists and non-extremists. These

efforts will improve our understanding of anti-tax beliefs and behaviors and aid in the development

of evidence-based intervention and prevention strategies.

Authors’ Note

Any opinions, findings, conclusions, or recommendations presented here are solely the author’s and

are not representative of DHS or the U.S. Government.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or

publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or

publication of this article: This research was supported by the U.S. Department of Homeland

Security (DHS) Science and Technology Directorate’s Office of University Programs and Resilient

Systems Division through the National Consortium for the Study of Terrorism and Responses to

Terrorism (START).

Notes

1. For a more detailed discussion of what constitutes a far-right extremist (FRE), see Freilich, Chermak, Belli,

Gruenewald, and Parkin (2014). In general, FRE subscribes to aspects of the following beliefs. They are

fiercely nationalistic, anti-global, suspicious of federal authority, and reverent of individual liberties, espe-

cially their right to own guns and be free of taxes. They believe in conspiracy theories involving imminent

threats to national sovereignty or personal liberty and believe that their personal or national “way of life” is

under attack. Sometimes, such beliefs are vague, but for some, the threat originates from specific racial or

religious groups. They believe that they must be prepared to defend against this attack by participating in

paramilitary training or survivalism).

2. See U.S. Internal Revenue Service (U.S. IRS 2018b) for a complete overview of frivolous tax arguments,

which fit under five broad categories: (1) voluntary nature of the federal income tax system (e.g., “there is no

legal requirement to pay taxes”), (2) meaning of taxable income (e.g., “certain types of income are not

taxable”), (3) meaning of terms used in Internal Revenue Code (e.g., “an individual is not a “citizen” or

“person” subject to tax law” or individual claims to be a sovereign citizen separate from the United States),

Sullivan et al. 507

(4) claims regarding constitutional amendments (e.g., invoking religious protections under the First Amend-

ment, due process and self-incrimination protections under the Fifth Amendment, taxes as form of slavery

outlawed by the Thirteenth Amendment, or argument that tax laws are unconstitutional because the Six-

teenth Amendment was not properly ratified), and (5) fictional legal arguments (e.g., slavery reparations,

IRS is a private corporation with no government authority, “corporation sole” through declaration as an

exempt religious entity, and the “redemption” or “straw man” conspiracy theory. The redemption or straw

man conspiracy theory, popular among sovereign citizens, states that the U.S. Treasury Department creates

secret bank accounts for each U.S. citizen called a straw man that can be utilized by those citizens to pay

taxes and other debts by using fake financial instruments (often fictitious Treasury checks known as a “sight

draft” or “bill of exchange”). The conspiracy theory also claims that Form 1099-OID can be sent to creditors,

who can present them to the Treasury to satisfy personal debts. For more information on sight drafts, bills of

exchange, or the redemption/straw man conspiracy theory, see Sanchez (2009), Southern Poverty Law

Center (SPLC, 2005, 2010), and U.S. Department of Treasury (2014).

3. See U.S. IRS’s (2018a) annual Dirty Dozen publication on the most popular tax fraud schemes.

4. These numbers do not include the 168 victims of the Oklahoma City Bombing.

5. Although there are differences between lone-wolf and loner offenders based on the attachment to an

informal or formal group (see Gruenewald et al., 2013b), this study does not distinguish between the two

and simply contrasts schemes committed by individual offenders with those involving co-offenders.

6. See Anti-Defamation League [ADL] (2012) and Sanchez (2009) for more information on the sovereign

citizen ideology. Much of this ideology stems from the anti-government, anti-Semitic Posse Comitatus

group from the 1970s, who originated the concept of “common law courts” to issue arrest warrants and

subpoenas to judges, law enforcement, and other officials. Sovereign citizens adhere to their own version of

the law, which is often a convoluted combination of the Magna Carta, the Bible, English common law, and

out of date constitutional law. They often use punctuation when spelling their name, especially to separate

the first and middle names from the “government issued” last name. Sovereign citizens believe the legit-

imate government was long ago replaced with an illegitimate government that entered into secret contracts

with citizens through various government requirements (e.g., driver’s license, zip code) to take away their

sovereignty. By renouncing their allegiance to this illegitimate government, proponents believe they can

reclaim their sovereignty and remove any authority the government holds over them (Anti-Defamation

League [ADL], 2012; Sanchez, 2009).

7. For a detailed explanation of the development of the Extremist Crime Database (ECDB), which also tracks

violent crimes and extremist groups, see Chermak, Freilich, Parkin, and Lynch (2012) and Freilich et al.

(2014). Recent studies have relied on the ECDB to examine the evolution of domestic extremist groups

(Freilich, Chermak, & Caspi, 2009), differences between violent and nonviolent extremist groups (Chermak,

Freilich, & Suttmoeller, 2013), comparisons between far-right homicides and “regular” nonextremist homi-

cides (Gruenewald & Pridemore, 2012), fatal attacks against the police (Freilich & Chermak, 2009; Sutt-

moeller, Gruenewald, Chermak, & Freilich, 2013), lone-wolf attacks (Gruenewald et al., 2013a, 2013b),

ideologically motivated homicide victimization (Parkin & Freilich, 2015; Parkin, Freilich, & Chermak,

2015), county-level variation in the location of extremist attacks (Chermak & Gruenewald, 2015; Freilich,

Adamczyk, Chermak, Boyd, & Parkin, 2015), and financial and material support schemes committed by

jihadi extremists (Sullivan, Freilich, & Chermak, 2014).

8. Generally, cases where the prosecutor drops charges are included in the ECDB, but charges not pursued by

the police are not included. Any criminal offenses related to these crimes are applicable, but typically

include tax evasion, failure to file an income tax return, or conspiracy to impede the administration of

internal revenue laws. In addition, we operationalize financial crimes broadly and include crimes that are

financially related but may not be traditionally considered financial crimes. The most prominent examples

are the filing of false liens and other legal and tax documents. False liens, known as a type of paper terrorism,

are legally binding financial obligations filed against a debtor, which are intended to cause financial harm to

the victim. Both types of crimes are considered financial schemes for the purposes of this study.

508 Criminal Justice Review 44(4)

9. In numerous cases, the source materials referred to a certain number of individuals involved in the scheme

but did not mention their names. While these unknown offenders are coded in ECDB, they were removed

from the current study if their identity could not be established.

10. ECDB has developed specialized search protocols using the following search engines: LexisNexis; Pro-

Quest; Yahoo; Google; Copernic; News Library; InfoTrac; Google Scholar; Amazon; Google U.S. Gov-

ernment; Federation of American Scientists; Google Video; Center for the Study of Intelligence; Surf Wax;

Dogpile; Mamma; Librarians’ Internet Index; Scirus; All the Web; Google News; Google Blog; Homeland

Security Digital Library, VINElink; Inmate Locator; Bureau of Prisons; Individual State Departments of

Corrections; Black Book Online; Quatloos; ADL; SPLC; and Center on Law and Security.

11. For examples of the use of the strength of Ideological Association Scale, see Belli (2011) and Sullivan,

Chermak, Wilson, and Freilich (2014). The same strength of association score was used to evaluate the

ideological connection of the scheme. If any evidence directly contradicts the ideological association, such

as is the case with many anti-tax schemes, it was included as con evidence on the Ideology Strength Scale

would be decreased at least a score of 2. The score would decrease to “1” if only a single piece of pro

evidence was identified. Profit motive could potentially undermine the extremist connection only if it was

egregious and appeared to be the main reason for engaging in an anti-tax scheme, where the same

arguments used to promote the scheme were also used to establish the offender’s extremist ideology. If

not, evidence of profit motive would not count as contradictory evidence. Simply participating in an anti-

tax scheme by avoiding taxes is not counted as contradictory evidence. An egregious profit motive is

necessary to establish contradictory evidence according to the Ideological Association Scale.

12. The ideological evidence must be intrinsically tied to the profit motivation to count as contradictory

evidence. This occurs when anti-tax beliefs used during a financial scheme undermine the evidence for

a profit motive, in which case the profit and ideology scores may be similar for extremists involved in anti-

tax schemes. An individual could be high on both the Profit and Ideological Scales, such as in the example

where a White supremacist engaged in a profit-motivated check fraud scheme. In this case, the profit score

is high because the interest in personal financial gain through fraud, but the White supremacist views do not

undermine this profit motivation for engaging in the check fraud scheme and therefore would not be

counted as contradictory evidence.

13. Due to the difficultly of reliably assessing exact start and end dates for schemes, our measure counts

scheme activity distinctly for each calendar. In the five cases where start dates could not be verified, the end

year was coded as the start year with a length of one. If the scheme was active during a calendar year, it was

counted as 1 year. The start year was then subtracted from the end year for a total number of years active.

14. These numbers may be skewed somewhat by the initial sampling decision to include schemes active

between 2002 and 2004, suggesting this trajectory is not entirely surprising. However, the active schemes

in the study universe roughly mirrored the trajectory of all schemes involving tax protesters in the U.S.

Extremist Financial Crime Database, so this pattern can be generalized to all financial crime schemes

linked to the anti-tax movement.

15. Race for 11% (n¼ 41) of the offenders could not be determined. Black nationalists, such as those adhering

to the “Moorish” ideology, did not fit the ECDB’s description of FRE and were therefore excluded from the

current study but are captured by the ECDB as their own distinct category. Black nationalists have used

many similar tactics as sovereign citizens, such as tax avoidance, redemption, and real estate fraud (e.g.,

house squatting). Numerous sources describe them as sovereign citizens and they have even worked

together directly in some cases. This is an issue for future research and beyond the scope of the current

study.

16. Age was recorded for each nonunique offender at both the start and end of their schemes. Each offender

received a separate record for each scheme to obtain an accurate age count for each offender at the time

they were committing their crimes, which is why the number of nonunique offenders for age is higher than

the total number of unique individuals. Start and end ages could not be determined for eight and five

nonunique offenders, respectively.

Sullivan et al. 509

17. These extremes are logical according to the scale design, as profit-motivated schemes cannot have evi-

dence for ideology and vice versa. Any evidence to the contrary automatically reduces the strength score to

“2,” resulting in a scheme with mixed motivations (mixed motivations could also be a “1” score). Most of

the profit scores reflect a single piece of pro evidence favoring a profit motivation. This results in scores of

either “3” or “1” (“1” in cases where ideological evidence contradicts the profit motive). This is largely due

to two factors. The first is the difficulty in establishing multiple pieces of profit evidence compared to

ideological, which is more clearly defined than profit evidence. The second is the comparative amount of

time spent addressing ideological association compared to profit. The ECDB focuses vast resources on

identifying extremist connections, resulting in ideological associations and motivations being more clearly

defined than other motivational types. Other motivations connected with ideology, such as psychological

and social characteristics as well as retaliation and revenge, are usually tied with and coded as ideology

unless they distinctly and notably differ.

18. Independent t test: ideology, t(211) ¼ �0.581, p ¼ .562 (lone wolf: M ¼ 2.807, SD ¼ 1.302, n ¼ 140, and

multioffender: M ¼ 2.699, SD ¼ 1.277, n ¼ 73), and profit, t(211) ¼ 1.715, p ¼ .088 (lone wolf: M ¼ 0.

479, SD ¼ 0.861, n ¼ 140, and multioffender: M ¼ 0.695, SD ¼ 0.882, n ¼ 73).

19. Independent t test: ideology strength, t(211)¼�3.981, p¼ .000 (tax: M¼ 2.926, SD¼ 1.191, n¼ 176, and

nontax: M¼ 2.027, SD¼ 1.500, n¼ 39); and profit strength, t(211)¼ 4.458, p¼ .000 (tax: M¼ 0.434, SD

¼ 0.691, n ¼ 176, and nontax: M ¼ 1.108, SD ¼ 1.329, n ¼ 39).

20. Independent t test: ideology strength, t(211)¼ 3.480, p¼ .001 (investment: M¼ 1.250, SD¼ 1.389, n¼ 8,

and noninvestment: M ¼ 2.829, SD ¼ 1.254, n ¼ 205); and profit strength, t(211) ¼ �5.558, p ¼ .000

(investment: M ¼ 2.125, SD ¼ 1.458, n ¼ 8, and noninvestment: M ¼ 0.490, SD ¼ 0.785, n ¼ 205).

21. As motives varied across schemes, offenders involved in multiple schemes were coded separately for each

unique scheme. This resulted in a total of 427 nonunique offenders with identifiable motives. While

motives were permitted to vary by scheme, individuals coded as extremist remained consistent across all

schemes regardless of motive or evidence at the time. If additional schemes with unclear motives were

identified, motive was coded as unknown. Nearly all offenders with unknown motivations (88%) were

nonextremist. The three extremists with unknown or other motives were involved in prior financial

schemes where the motivation could not be established.

22. This is partially an artifact of the operationalization of the association strength variables as scores of “1” or

“2” for nonextremists were not possible. Single pieces of evidence supporting the profit connection were

more likely than multiple indicators, as ideology indicators more readily identifiable than profit evidence.

Few extremists (n ¼ 7, 2%) had high-profit strength scores of “3” or “4” while 24% had “1” profit scores.

Indicators of a profit association for engaging in financial schemes should receive further attention in future

studies.

23. In these cases, an extremist connection was established, but the motive for the specific scheme was profit.

That is, their scheme activities were not intrinsically tied to their ideology, so profit did not undermine the

ideological connection and vice versa. However, the opposite is true when anti-tax arguments are used to

conduct a large-scale tax avoidance scheme motivated by profit. Typically, schemes involving large

numbers of offenders with profit motives are either mixed or profit motivated, although they could be

involved in an ideologically motivated scheme where the main perpetrators driving the scheme are ideo-

logically motivated.

24. Due to the complex nature of measuring financial schemes, temporal patterns should be interpreted

cautiously. These schemes took place over prolonged periods of time and accounting for them is difficult

without a quantifiable measure, such as the number of annual indictments or convictions. However, this

measure would not reflect the actual timing of the activities and only the end date. When an indictment is

issued, it reflects all the years where schemes are active. For instance, indictments issued after 2010 reflect

financial scheme activities from the late 2000s. Given their nature, these numbers will increase as future

financial crimes are identified and processed through the criminal justice system.

510 Criminal Justice Review 44(4)

References

Anti-Defamation League. (2005). Extremism in America: Tax protest movement. New York, NY: Author.

Retrieved from http://www.adl.org/learn/ext_us/TPM.asp?xpicked¼4&item¼21

Anti-Defamation League. (2012). The lawless ones: The resurgence of the sovereign citizen movement. New

York, NY: Author. Retrieved from http://www.adl.org/assets/pdf/combating-hate/Lawless-Ones-2012-

Edition-WEB-final.pdf

Agnew, R. (2016). General strain theory and terrorism. In G. LaFree & J. D. Freilich (Eds.), Handbook on the

criminology of terrorism (pp. 121–132). Hoboken, NJ: Wiley Press.

Akins, J. K., & Winfree, L. T. (2016). Social learning theory and becoming a terrorist: New challenges

for a general theory. In G. LaFree & J. D. Freilich (Eds.), Handbook on the criminology of terrorism

(pp. 133–149). Hoboken, NJ: Wiley Press.

Barkun, M. (2007). Purifying the law: The legal world of “Christian Patriots.” Journal for the Study of

Radicalism, 1, 57–70.

Belli, R. (2011). Where political extremist and greedy criminal meet: A comparative study of financial crimes

and criminal networks in the United States (PhD dissertation). John Jay College, The City University of New

York, New York. Retrieved from http://www.ncjrs.gov/App/Publications/abstract.aspx?ID¼256482

Belli, R., & Freilich, J. D. (2009). Situational crime prevention and non-violent terrorism: A “soft” approach

against ideologically motivated tax-refusal. Crime Prevention Studies, 25, 173–206.

Braithwaite, V. (2010). Criminal prosecution within responsive regulatory practice. Criminology & Public

Policy, 9, 515–523.

Carter, D. L., Chermak, S. M., Carter, J. G., & Drew, J. (2014). Understanding law enforcement intelligence

processes. College Park, MD: START. Retrieved from http://www.start.umd.edu/pubs/START_Understan

dingLawEnforcementIntelligenceProcesses_July2014.pdf

Chermak, S. M., Freilich, J. D., Parkin, W. S., & Lynch, J. P. (2012). American terrorism and extremist crime

data sources and selectivity bias: An investigation focusing on homicide events committed by far-right

extremists. Journal of Quantitative Criminology, 28, 191–218.

Chermak, S. M., Freilich, J. D., & Simone, J. (2010). Surveying American state police agencies about lone

wolves, far-right criminality, and far-right and Islamic jihadist criminal collaboration. Studies in Conflict

and Terrorism, 33, 1019–1041.

Chermak, S. M., Freilich, J. D., & Suttmoeller, M. (2013). The organizational dynamics of far-right hate groups

in the United States: Comparing violent to nonviolent organizations. Studies in Conflict & Terrorism, 36,

193–218.

Chermak, S. M., & Gruenewald, J. (2015). Laying the foundation for the criminological examination of right-

wing, left-wing, and Al Qaeda inspired extremism in the United States. Terrorism & Political Violence, 27,

133–159.

Dahl, E. J. (2011). The plots that failed: Intelligence lessons learned from unsuccessful terrorist attacks against

the United States. Studies in Conflict & Terrorism, 34, 621–648.

Fitzpatrick, K. M., Gruenewald, J., Smith, B. L., & Roberts, P. (2016). A community-level comparison of

terrorism movements in the United States. Studies in Conflict & Terrorism, 40, 399–418.

Flynn, K., & Gerhardt, G. (1995). The silent brotherhood: The chilling inside story of America’s violent anti-

government militia movement. New York, NY: Signet/Penguin.

Freilich, J. D. (2003). American militias: State-level variations in militia activities. New York, NY: LFB

Scholarly.

Freilich, J. D., Adamczyk, A., Chermak, S. M., Boyd, K., & Parkin, W. S. (2015). Investigating the applicability

of macro-level criminology theory to terrorism: A county-level analysis. Journal of Quantitative Crimin-

ology, 31, 383–411.

Freilich, J. D., Almanzar, N. A. P., & Rivera, C. J. (1999). How social movement organizations explicitly and

implicitly promote deviant behavior: The case of the militia movement. Justice Quarterly, 16(3), 655–683.

Sullivan et al. 511

Freilich, J. D., & Chermak, S. M. (2009). Preventing deadly encounters between law enforcement and

American far-rightists. Crime Prevention Studies, 25, 141–172.

Freilich, J. D., Chermak, S. M., Belli, R., Gruenewald, J., & Parkin, W. S. (2014). Introducing the United States

Extremist Crime Database (ECDB). Terrorism & Political Violence, 26, 372–384.

Freilich, J. D., Chermak, S. M., & Caspi, D. (2009). Critical events in the life trajectories of domestic extremist

groups: A case study analysis of four violent white supremacist groups. Criminology & Public Policy, 8,

497–530.

Freilich, J. D., Chermak, S. M., Gruenewald, J., Parkin, W. S., & Klein, B. R. (2018). Patterns of fatal extreme-

right crime in the United States. Perspectives on Terrorism, 12(6), 38–51.

Freilich, J. D., Chermak, S. M., & Simone, J. (2009). Surveying American state police agencies about terrorism

threats, terrorism sources, and terrorism definitions. Terrorism and Political Violence, 21, 450–475.

Freilich, J. D., & Pridemore, W. A. (2005). A reassessment of state-level covariates of militia groups. Beha-

vioral Sciences and the Law, 23, 527–546.

Gill, P., Lee, J., Rethemeyer, R. K., Horgan, J., & Asal, V. (2014). Lethal connections: The determinants of

network connections in the Provisional Irish Republican Army 1970-1998. International Interactions:

Empirical and Theoretical Research in International Relations, 40, 52–78.

Gruenewald, J. A., Chermak, S. M., & Freilich, J. D. (2013a). Distinguishing “loner” attacks from other

domestic extremist violence: A comparison of far-right homicide incident and offender characteristics.

Criminology & Public Policy, 12, 63–91.

Gruenewald, J. A., Chermak, S. M., & Freilich, J. D. (2013b). Far-right lone wolf homicides in the United

States. Studies in Conflict and Terrorism, 36, 1005–1024.

Gruenewald, J. A., Freilich, J. D., & Chermak, S. M. (2009). An overview of the domestic far-right and its

criminal activities. In B. Perry & R. Blazak (Eds.), Hate crimes: Hate crime offenders (pp. 1–21). Westport,

CT: Praeger.

Gruenewald, J. A., & Pridemore, W. A. (2012). A comparison of ideologically-motivated homicides from the

new Extremist Crime Database and homicides from the Supplementary Homicide Reports using multiple

imputation by chained equations to handle missing values. Journal of Quantitative Criminology, 28,

141–162.

Hamm, M. S. (2011). Prisoner radicalization and sacred terrorism: A life-course perspective. In R. Rosenfeld,

K. Quinet, & C. Garcia (Eds.), Contemporary issues in criminological theory and research: The role

of social institutions: Presidential papers from the 2010 American Society of Criminology Conference

(pp. 173–204). Belmont, CA: Wadsworth.

Leighton, P. (2010). Fairness matters-more than deterrence: Class bias and the limits of deterrence. Criminol-

ogy & Public Policy, 9, 525–533.

Levi, M. (2010). Serious tax fraud and noncompliance: A review of evidence on the differential impact of

criminal and noncriminal proceedings. Criminology & Public Policy, 9, 493–513.

McCauley, C., & Moskalenko, S. (2008). Mechanisms of political radicalization: Pathways toward terrorism.

Terrorism & Political Violence, 20, 415–433.

McCauley, C., & Moskalenko, S. (2011). Friction: How radicalization happens to them and us. New York, NY:

Oxford University Press.

McCauley, C., & Moskalenko, S. (2014). Toward a profile of lone wolf terrorists: What moves an individual

from radical opinion to radical action. Terrorism & Political Violence, 26, 69–85.

Parkin, W. S. (2012). Developing theoretical propositions of far-right ideological victimization (Doctoral

dissertation). John Jay College, Graduate Center, CUNY, New York.

Parkin, W. S., & Freilich, J. D. (2015). Routine activities and right-wing extremists: An empirical comparison

of the victims of ideologically and non-ideologically motivated homicides committed by American far-

rightists. Terrorism & Political Violence, 27, 182–203.

Parkin, W. S., Freilich, J. D., & Chermak, S. M. (2015). Ideological victimization: Homicides perpetrated by

far-right extremists. Homicide Studies, 19, 211–236.

512 Criminal Justice Review 44(4)

Pitcavage, M. (1998). Paper terrorism’s forgotten victims: The use of bogus liens against private individuals

and business. New York, NY: Anti-Defamation League. Retrieved from http://www.adl.org/mwd/

privlien.asp

Pitcavage, M. (1999). Old wine, new bottles: Paper terrorism, paper scams and paper “redemption.”

New York, NY: Anti-Defamation League. Retrieved from http://www.adl.org/mwd/redemption.asp

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

Sageman, M. (2004). Understanding terror networks. Philadelphia, PA: University of Pennsylvania Press.

Sanchez, C. (2009). Sovereign citizens movement resurging: Resurgence of far-right movement reported

(Intelligence Report, Issue 133). Montgomery, AL: Southern Poverty Law Center. Retrieved from https://

www.splcenter.org/fighting-hate/intelligence-report/2009/sovereign-citizens-movement-resurging

Spaaij, R. (2010). The enigma of lone wolf terrorism: An assessment. Studies in Conflict & Terrorism, 33,

854–870.

Southern Poverty Law Center. (2005). His “straw man” free, a scammer finds the rest of him isn’t: Patriots for

profit (Intelligence Report, Issue 118). Montgomery, AL: Author. Retrieved from http://www.splcenter.org/

get-informed/intelligence-report/browse-all-issues/2005/summer/patriots-for-profit

Southern Poverty Law Center. (2010). The sovereign: A dictionary of the peculiar (Intelligence Report, Issue

139). Montgomery, AL: Author. Retrieved from http://www.splcenter.org/get-informed/intelligence-report/

browse-all-issues/2010/fall/sovereign-idioticon-a-dictionary-of-the

Sullivan, B. A., Chermak, S. M., Wilson, J. M., & Freilich, J. D. (2014). The nexus between terrorism and

product counterfeiting in the United States. Global Crime, 15, 357–378.

Sullivan, B. A., Freilich, J. D., & Chermak, S. M. (2014). Financial crime and material support schemes linked

to al-Qa’ida and Affiliated Movements (AQAM) in the United States: 1990 to June 2014. College Park, MD:

START. Retrieved from https://www.start.umd.edu/pubs/START_TEVUS_ECDB_Financial%20Cri

me%20and%20Material%20Support%20Schemes%20Perpetrated%20by%20Supporters%20of%20AQA

M_Nov2014.pdf

Sullivan, B. A., Freilich, J. D., & Chermak, S. M. (2015). Research brief: Financial crimes perpetrated by far-

right extremists in the United States: 1990-2013. College Park, MD: START. Retrieved from http://

www.start.umd.edu/pubs/START_ECDB_FinancialCrimesSchemesPerpetratedbyFarRightExtremists_

June2015.pdf

Sullivan, B. A., Freilich, J. D., & Chermak, S. M. (2016). Financial terror: Financial crime schemes involving

extremists linked to the American Far-Right and al-Qa’ida and affiliated movements. In G. LaFree & J. D.

Freilich (Eds.), Handbook on the criminology of terrorism (pp. 420–432). Hoboken, NJ: Wiley Press.

Suttmoeller, M., Gruenewald, J. A., Chermak, S. M., & Freilich, J. D. (2013). Killed in the line of duty:

Comparing police homicides committed by far-right extremists to all police homicides. Law Enforcement

Executive Forum, 13, 45–64.

U.S. Department of Treasury. (2014). Bogus sight drafts/bills of exchange drawn on the treasury. Washington,

DC: Author. Retrieved from http://www.treasurydirect.gov/instit/statreg/fraud/fraud_bogussightdraft.htm

U.S. Government Accountability Office. (2008). Tax compliance: Businesses owe billions in federal payroll

taxes. Washington, DC: Author. Retrieved from https://www.gao.gov/assets/280/278637.pdf

U.S. Internal Revenue Service. (2018a). Dirty dozen. Washington, DC: Author. Retrieved from https://www.irs

.gov/newsroom/dirty-dozen

U.S. Internal Revenue Service. (2018b). The truth about frivolous tax arguments. Washington, DC: Author.

Retrieved from https://www.irs.gov/pub/taxpros/frivolous_truth_march_2018.pdf

Author Biographies

Brandon A. Sullivan is an assistant professor of criminology and criminal justice at Indiana University

Southeast. He is also a research associate of the Research Foundation of the City University of New York,

National Consortium for the Study of Terrorism and Responses to Terrorism (START), and the National

Sullivan et al. 513

White-Collar Crime Research Consortium. He is co-principal investigator and project manager for the U.S.

Extremist Financial Crime Database (EFCDB), an open-source relational database of financial crimes com-

mitted by political and religious extremists in the United States. His research has been funded by the National

Institute of Justice and the Department of Homeland Security. His primary research interests include the crime–

terror nexus, criminal enterprises and networks, and white-collar and corporate crime.

Joshua D. Freilich is a professor of criminal justice at John Jay College. He is a creator and co-director of the

Extremist Crime Database (ECDB), an open-source relational database of violent and financial crimes com-

mitted by extremists in the United States; a creator and codirector of the School Shooting Database (SSDB), an

open-source relational database of school shootings in the U.S. resulting in at least one injury; and the chair

(2017–2019) of the American Society of Criminology’s Division on Terrorism and Bias Crimes. His research

has been funded by the Department of Homeland Security and the National Institute of Justice.

Steven M. Chermak is a professor of criminal justice at Michigan State University. He is the creator and

co-director of the U.S. Extremist Crime Database (ECDB), an open-source relational database of violent and

financial crimes committed by political extremists in the United States. His research includes activities in the

following areas: far-right extremism, the effectiveness of strategies used to prevent terrorism and crime, and the

media’s role in relation to crime and terrorism issues.

514 Criminal Justice Review 44(4)

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false /IncludeSlug false /Namespace [ (Adobe) (InDesign) (4.0) ] /OmitPlacedBitmaps false /OmitPlacedEPS false /OmitPlacedPDF false /SimulateOverprint /Legacy >> << /AllowImageBreaks true /AllowTableBreaks true /ExpandPage false /HonorBaseURL true /HonorRolloverEffect false /IgnoreHTMLPageBreaks false /IncludeHeaderFooter false /MarginOffset [ 0 0 0 0 ] /MetadataAuthor () /MetadataKeywords () /MetadataSubject () /MetadataTitle () /MetricPageSize [ 0 0 ] /MetricUnit /inch /MobileCompatible 0 /Namespace [ (Adobe) (GoLive) (8.0) ] /OpenZoomToHTMLFontSize false /PageOrientation /Portrait /RemoveBackground false /ShrinkContent true /TreatColorsAs /MainMonitorColors /UseEmbeddedProfiles false /UseHTMLTitleAsMetadata true >> << /AddBleedMarks false /AddColorBars false /AddCropMarks false /AddPageInfo false /AddRegMarks false /BleedOffset [ 9 9 9 9 ] /ConvertColors /ConvertToRGB /DestinationProfileName (sRGB IEC61966-2.1) /DestinationProfileSelector /UseName /Downsample16BitImages true /FlattenerPreset << /ClipComplexRegions true /ConvertStrokesToOutlines false /ConvertTextToOutlines false /GradientResolution 300 /LineArtTextResolution 1200 /PresetName ([High Resolution]) /PresetSelector /HighResolution /RasterVectorBalance 1 >> /FormElements true /GenerateStructure false /IncludeBookmarks false /IncludeHyperlinks false /IncludeInteractive false /IncludeLayers false /IncludeProfiles true /MarksOffset 9 /MarksWeight 0.125000 /MultimediaHandling /UseObjectSettings /Namespace [ (Adobe) (CreativeSuite) (2.0) ] /PDFXOutputIntentProfileSelector /DocumentCMYK /PageMarksFile /RomanDefault /PreserveEditing true /UntaggedCMYKHandling /UseDocumentProfile /UntaggedRGBHandling /UseDocumentProfile /UseDocumentBleed false >> ] /SyntheticBoldness 1.000000 >> setdistillerparams << /HWResolution [288 288] /PageSize [612.000 792.000] >> setpagedevice