Citizenship Status and Arrest Patterns for Violentand Narcot

Citizenship Status and Arrest Patterns for Violent
and Narcotic-Related Offenses in Federal Judicial
Districts along the U.S./Mexico Border
Deborah Sibila1 & Wendi Pollock2 & Scott Menard3
Received: 8 September 2016 /Accepted: 30 October 2016 /
Published online: 10 November 2016
# Southern Criminal Justice Association 2016
Abstract Media reports routinely reference the drug-related
violence in Mexico,
linking crime in communities along the Southwest U.S. Border
to illegal immigrants.
The primary purpose of the current research is to examine
whether the media assertions
can be supported. Logistic regression models were run to
determine the impact of
citizenship on the likelihood of disproportionate arrest for
federal drug and violent
crimes, along the U.S./Mexico border. In arrests for homicide,
assault, robbery, and
weapons offenses, U.S. citizens were disproportionately more
likely than non-citizens
to be arrested. The only federal crime where non-citizens were
disproportionately more
likely to be arrested than were U.S. citizens was for marijuana
offenses. Results of the
current study challenge the myth of the criminal immigrant.
Keywords Citizenship . Arrest . Criminal immigrant . Gender

The myth of the criminal immigrant is perhaps one of the single
most controversial
factors contributing to America’s present day anti-immigrant
fervor. In their book, The
Am J Crim Just (2017) 42:469–488
DOI 10.1007/s12103-016-9375-1
* Wendi Pollock
[email protected]
Deborah Sibila
[email protected]
Scott Menard
[email protected]
1 Department of Government, Stephen F. Austin State
University, Box 13045 SFA Station,
Nacogdoches, TX 75962, USA
2 Department of Social Sciences, Texas A&M University, 6300
Ocean Drive, Corpus Christi,
TX 78412, USA
3 Institute of Behavioral Science, University of Colorado,
Boulder, USA
http://crossmark.crossref.org/dialog/?doi=10.1007/s12103-016-
9375-1&domain=pdf
Immigration Time Bomb, authors Richard D. Lamm and Gary
Imhoff contend that the
issue of immigration and crime is a critically divisive topic
easily subject to misinter-
pretation (1985, p. 21). The belief that immigrants are more
crime-prone than native-
born is not a twentieth century development. Debates on this

controversy date back
more than 100 years (Hagan & Palloni, 1998; Martinez & Lee,
2000). Hagan and
Pallon believed that the nexus between immigration and crime
is so misleading that it
constitutes a mythology (1999, p. 630). In a special report for
the Immigration Policy
Center, professors Ruben Rumbaut and Walter Ewing wrote
B[The] misperception that
the foreign-born, especially illegal, immigrants are responsible
for higher crime rates is
deeply rooted in American public opinion and sustained by
media anecdote and
popular myth^ (2007, p. 3). Lee (2013) similarly argues that
immigrants have a long
history of serving as scapegoats for a vast array of America’s
societal problems
including crime.
Public opinion surveys suggest that a significant number of
Americans believe that
immigrants, particularly illegal immigrants, are associated with
higher crime rates
(Kohut et al., 2006; Muste, 2013; Sohoni & Sohoni, 2014).
Media sources routinely
associate immigration, especially Hispanic immigrants, with
crime (Bender, 2003;
Martinez, 2002). Politicians also play a key role in perpetuating
the belief that
immigrants and crime are interrelated. Arizona Governor Jan.
Brewer, Senator John
McCain and former presidential hopeful Patrick Buchanan are
just a few political
figures that have gone on record linking immigration directly
with high crime rates
(Butcher & Piehl, 1998; USA Today, 2011). On May 15, 2006,

during a presidential
address to the nation on immigration reform, former President
George W. Bush
asserted that BIllegal immigration puts pressure on public
schools and hospitals, it
strains state and local budgets and brings crime to our
communities.^ According to
Rumbaut and Ewing (2007), regardless of the much-publicized
media stereotyping
and harsh political rhetoric, empirical evidence simply does not
support the popular
misperception that immigration is the cause of higher crime
rates in America.
History of Immigration and Crime Theory and Research
Explanations of the link between immigration and crime have
been offered from the
perspectives of culture conflict, acculturation, social
disorganization and the
immigration revitalization perspective. From the culture conflict
perspective, Sellin
(1938) suggested that the conflict between the norms of
behavior for divergent
cultures, as represented by native born Americans versus
immigrants, was one source
of crime. Sutherland (1924, 1934) posited that it was not
immigration itself, but rather
acculturation, that led to the association between immigration
and crime, and noted
that second-generation immigrants had higher crime rates than
first-generation immi-
grants. From the social disorganization perspective, researchers
from the Chicago
School linked immigration to a number of social issues,
including not only crime but

also poverty, unemployment, poor housing, and substandard
schools (Park et al.,
1925; Shaw, 1929; Shaw & McKay, 1931, 1942; Thomas &
Znaniecki, 1920,
1958). Shaw and McKay, in particular, suggested that it was not
the characteristics
of the immigrants themselves, but the characteristics of the
urban neighborhoods in
which they resided, that led to the apparent link between
immigration and crime (see
470 Am J Crim Just (2017) 42:469–488
also Taylor, 1931). In contrast to the culture conflict,
acculturation, and social
disorganization perspectives, the immigration revitalization
perspective (Lee, 2013;
Martinez, 2006) suggests that immigrants tend to be less
criminal than native-born
Americans, and that the informal social controls that are an
integral part of the culture
in predominantly immigrant neighborhoods result in higher
levels of social organiza-
tion and lower rates of crime. The present paper is informed by,
but not a direct test
of, these theories, which disagree about whether immigrants
should have dispropor-
tionately higher (culture conflict, social disorganization;
acculturation for the second
generation), or lower (immigrant revitalization; acculturation
for the first generation)
involvement in illegal behavior.
Early empirical investigations into the link between

immigration and crime were
limited and were focused at the individual level (Abbott, 1915;
Hourwich, 1912; Lind,
1930; Taft, 1933, 1936; Van Vechten, 1941). These studies
found little evidence of a
causal relationship between immigration and crime. Three major
government commis-
sions (the Industrial Commission of 1901, the [Dillingham]
Immigration Commission
of 1911, and the [Wickersham] National Commission on Law
Observance and
Enforcement of 1931) similarly explored the issue of whether
immigration increases
crime. Each of the commissions found that immigrants were less
likely to commit
crime than were their native-born counterparts.
More recent studies investigating the association between
immigration and crime
tend to agree with earlier research, specifically that immigrants
are not disproportion-
ately involved in crime and are oftentimes significantly less
involved than native-born
Americans (Hagan & Palloni, 1998; Martinez & Lee, 2000;
Mears, 2002; Rumbaut &
Ewing, 2007). Contemporary researchers examining the
immigrant-violent crime
nexus have concentrated their efforts on macro-level studies,
conducting both neigh-
borhood and city-level studies. Findings from macro-level
research surrounding the
immigration-violent crime question have been more inconsistent
than the individual-
level studies. There are a handful recent studies that find some
positive relationships
when examining the impact of immigration and certain crime

variables under specific
conditions (Lee, et al., 2000; Martinez, 2000, 2003; Sampson &
Raudenbush, 1999).
A significant portion of contemporary research examining the
relationship between
immigration and crime has focused on ethnic gangs and violent
crime, especially
homicide. More recently, researchers have explored the idea
that immigration has
actually contributed to the decline in U.S. crime rates since the
1990s (Sampson,
2006, 2008). In addition to recent academic studies, at least one
government com-
mission was tasked with examining the issue of immigration and
crime during the last
20 years. The U.S. Commission on Immigration Reform (1994)
examined the impact
of Mexican immigration on crime rates in metropolitan areas
along the Southwest
border as compared to those in non-border cities. The
commission found that crimes
rates were typically lower in cities with large Mexican
populations along the border
than for non-border cities.
The Southwest Border
Because of the current study’s focus on the impact of immigrant
status on violent
crime and narcotic-related offenses in federal jurisdictions
along the United States-
Am J Crim Just (2017) 42:469–488 471

Mexico border during a time of unprecedented drug violence in
Mexico, it is
important to provide some background information regarding
the location and
timeframe for the research. The U.S.-Mexico border commonly
referred to, as the
Southwest border is an international boundary separating the
United States and
Mexico. The border was created in 1848 after the end of the
Mexican-American
War under the Treaty of Guadalupe-Hidalgo. The Southwest
border is one of the
longest borders in the world (1954 miles) and runs along the
U.S. states of
California, Arizona, New Mexico and Texas on the northern
side and the Mexican
states of Baja California, Sonora, Chihuahua, Coahuila, Nuevo
Leon and Tamaulipas
on the southern side. It is also considered to be the busiest
international boundary in
the world (Andreas, 2000). The La Paz Agreement signed by the
United States and
Mexico in 1983 specifies that the Bborder region^ between the
U.S.-Mexico en-
compass the band of land that stretches 100 km (approximately
62.5 miles) on either
side of the boundary line. There were approximately 70.9
million residents living in
the four border states in 2010, with approximately 7.5 million
people residing in 37
counties that comprise the border region (Rex, 2014). According
to the U.S. Census
Bureau, the border region contains the largest concentration of
Hispanic population
in the country — from 25 % to more than 50 % of the
population (Ennis et al.,

2011). The Pew Research Center estimates that in 2010
approximately 4.7 million
illegal immigrants lived in the four states along the Southwest
border (Passel &
Cohn, 2011).
The movement of illegal drugs and movement of unauthorized
immigrants from
Mexico into the United States via Southwest border have long
been areas of
contention in U.S.-Mexico relations (Andrews, 2012;
Domínguez & De Castro,
2009; Payan, 2006; Seelke, 2010). For decades, marijuana and
heroin (primarily
Mexican brown and black tar heroin) were smuggled across the
border without
significant interference by law enforcement in either country
(Andreas, 2000).
During the 1980s, Mexico became an important transshipment
center for drugs
entering the United States following the crackdown on the
importation of
Colombian cocaine and marijuana through South Florida. The
crackdown led to
the redirection of federal drug interdiction efforts from South
Florida to the
Southwest border. The passage of the Immigration Reform and
Control Act of
1986, or IRCA, which granted amnesty to millions of
undocumented immigrants
living in the United States, further contributed to public
scrutiny of Southwest
border issues and the problem of undocumented immigration
(Immigration Reform
and Control Act of 1986, n.d.). Efforts by law enforcement
agencies to curb further

illegal immigration across the Southwest border following the
passage of the IRCA
legislation proved essentially futile (Payan, 2006). During the
1990s, the U.S.
federal government increased the number and scope of
interdiction operations
targeting both drugs and illegal immigrants attempting to cross
the United States-
Mexico border (e.g., Operations Gate Keeper, Hold the Line,
Safeguard, and Rio
Grande). These operations made little inroad into the drug and
immigration prob-
lems plaguing the border region (Andrews, 2012; Domínguez &
De Castro, 2009;
Payan, 2006). Meanwhile, Mexico’s efforts to curb the
expansion of drug cartel
influence during the 1990s were largely ineffective. The cartels
expanded their
influence throughout Mexico, and drug-related corruption was
rampant throughout
the country’s government, police organizations and military
(Andreas, 2000;
472 Am J Crim Just (2017) 42:469–488
Carpenter, 2009). The U.S. federal government dramatically
escalated border polic-
ing following the 9/11 terrorist attacks in New York and
Washington. Perhaps the
most affected area in the U.S. after the attacks was the
Southwest border (Payan,
2006, p. 13; see also Domínguez & De Castro, 2009). National
security concerns
following 9/11 led to the tightening of border security checks,

hardening of land and
sea points of entry, crackdowns on unauthorized immigration
and increased
militarization of the border. Despite all these safeguards, public
perception that
government and law enforcement efforts to secure the
Southwest border are
substantially ineffectual persists. Cornelius (2005) suggests that
the government’s
efforts to secure the border are not only inadequate, but have
been more effective
keeping illegal immigrants inside the U.S. than acting as an
deterrent to others
attempting to enter the country (p. 12). Americans remain
divided over how to stem
the flow of illegal immigrants across the Southwest border.
The current image of the Southwest border as a region plagued
by violence and
crime is intrinsically linked to the rising tide of drug-related
violence in Mexico
during the last ten years (Beittel, 2009, 2011; Carpenter, 2012;
Payan, 2006).
Violence in Mexico significantly worsened following Mexico’s
President Felipe
Calderon’s declaration of war against his country’s drug cartels
shortly after his
inauguration in December 2006. The level of drug-related
crimes (i.e., homicides,
kidnappings, home invasions, drive-by shootings) increased
throughout Mexico,
particularly in the northern territories along the United States
border (Beittel, 2009,
2011; Domínguez & De Castro, 2009). According to Human
Rights Watch (2013),
approximately 60,000 Mexicans lost their lives as a result of

drug-related violence
during President Calderon’s tenure as president (2006–2012).
Since 2007, the media in United States, especially those along
the Southwest
border have been preoccupied with the drug violence and
bloodshed in Mexico
(Andrews, 2012; del Bosque, 2009). Media sources routinely
sensationalize re-
ports of U.S. citizens dying and being kidnapped in suspected
drug-related
incidents in cities along the Southwest border. The media
coverage has persuaded
Americans that the turmoil in Mexico is no longer confined to
that country
(Correa-Cabrera, 2012). Many are convinced that Mexico’s
drug-related violence
has Bspilled over^ into communities along the Southwest
border. ‘Spillover’ has
become a new media buzzword (del Bosque, 2009). While there
is no firm
definition for the term spillover violence it is generally
understood to be violence
that occurs as a result of drug trafficking. Civilians, law
enforcement officers and
other criminals or criminal organizations can all be the targets
of spillover
violence (Lee & Olson, 2013, p. 100). There is some debate as
to whether
spillover violence is an actual phenomenon (Correa-Cabrera,
2012; Lee &
Olson, 2013). Without a concise definition, the ability of law
enforcement to
identify and measure spillover violence is problematic. In a
report to Congress
regarding the issue of Southwest border violence, Finklea and

colleagues note that
Bno comprehensive, publicly available data exists that can
definitively answer the
question of whether there has been a significant spillover of
drug trafficking-
related violence into the United States^ (2010, p. 19). Further
complicating the
issue of spillover violence has been the media linkage of the
problem to the
Bflood^ of unauthorized immigrants moving across the
Southwest border (del
Bosque, 2009). Proponents of stricter immigration controls
argue that increased
Am J Crim Just (2017) 42:469–488 473
border security will significantly impede the flow of
undocumented immigrants
thereby reducing rates of violent and property crimes in border
communities
(Nevins, 2002; Payan, 2006).
The Federal Criminal Justice System and the Southwest Border
Criminal offenses occurring along the Southwest border can be
prosecuted in
either state or federal court. The primary trial court in the
federal judiciary is
the U.S. district court. There are currently 94 federal judicial
districts in the United
States, each with its own district court. Each district has
different judges, court-
house cultures and specialized local needs (Abrams et al.,
2010). There are five

federal districts along the Southwest border: The District of
Arizona, the District
of New Mexico, the Southern District of California, the
Southern District of
Texas, and the Western District of Texas (Fig. 1).
Each district has its own U.S. Attorney. The U.S. Attorneys’
Office (USAO)
represents the federal government in all cases where the United
States is a party. It
has the discretion to decide whether federal charges will be
filed in a case or if the
case should be referred to the state system. Some factors that
may affect the
USAO’s choice between federal or state prosecution include: (1)
primary investi-
gative jurisdiction; (2) custody of the suspect; (3) possibility of
a duplicative
prosecution; (4) caseload and resources; (5) legal advantage;
and (6) inter-
agency relationships and relations among agents (Abrams et al.,
2010). Federal
crimes prosecuted by the USAO are listed under various titles
of the United States
Code (USC) including Title 18 (the primary criminal and penal
code of the U.S.
federal government) and Title 26 (the Internal Revenue Code).
Fig. 1 Counties in southwestern judicial districts
474 Am J Crim Just (2017) 42:469–488
Current Study

The following research questions will be addressed:
Research question 1. What are the characteristics (age, gender,
ethnicity, marital
status and citizenship) of individuals arrested for the following
federal offenses along
the U.S.-Mexico border?
& 1a.Homicide
& 1b. Assault
& 1c. Robbery
& 1d. Marijuana
& 1e. Hard Drugs
& 1f. Weapons
Research question 2. Are non-citizen arrestees
disproportionately more likely to be
arrested for any of the following offenses, when compared to
U.S. citizen arrestees?
& 1a.Homicide
& 1b. Assault
& 1c. Robbery
& 1d. Marijuana
& 1e. Hard Drugs
& 1f. Weapons
Data
Data for the current study comes from the Federal Justice
Statistics Program (FJSP):
Arrests and Bookings for Federal Offenses (2007–2010)
research series. The datasets
contain comprehensive information about suspects and
defendants processed in the
federal criminal justice system during fiscal years 2007 to 2010.

Offenders arrested for
federal offenses are transferred to the custody of the United
States Marshals Service
(USMS) for processing, transportation, and detention. The
current dataset was con-
structed from the USMS Prisoner Tracking System (PTS)
database. Records include
arrests made by federal law enforcement agencies (including the
USMS), state and
local agencies, and self-surrenders. The USMS uses the PTS
application to maintain
tracking information for all federal prisoners in USMS custody.
The PTS was imple-
mented by the USMS in March 1993 to maintain tracking
information for federal
prisoners and to monitor federal prisoners in state and local
detention facilities under
contract to the USMS. The PTS replaced the Prisoner
Population Management System.
The PTS contains information that is specific to each individual
prisoner, including the
prisoner’s personal data (e.g., gender, ethnicity, age, marital
status and citizenship
status), property, medical information, criminal information,
and location. Prisoners’
records are created using information derived from key source
documents (e.g., USMS
and other agency arrest sheets), and this information is entered
into the PTS.
The rationale for the location and time setting of this research
warrants some
discussion. While USMS arrest statistics are collected in all
federal judicial districts
Am J Crim Just (2017) 42:469–488 475

nationwide, the current research will only utilize data from the
five federal districts on
the U.S.-Mexico border (Arizona, New Mexico, California
Southern, the Texas
Western and Southern Texas). The five Southwest border
districts accounted for
56 % of all federal suspects arrested and booked in the U.S. and
90 % of all
immigration arrests in 2010 (Motivans, 2012). This study
departs from most existing
research on immigration and crime, in that the focus is on a
variety of federal offenses
committed in five federal judicial districts whose jurisdiction
extends to multiple states
along the Southwest border. Previous research has almost been
exclusively limited to
examining a limited number of offenses (i.e. homicide) at either
the city or neigh-
borhood level (Martinez, 2006). The time period covered by this
research (2007–
2010) is significant because it covers a period of unprecedented
drug violence in
Mexico that was thought to contribute to crime levels in states
along the Southwest
border. Media reports routinely referenced the drug-related
violence in Mexico,
linking crime in communities along the Southwest border to
drug cartel members
and illegal immigrants.
Variables
The dependent variables in this study are six different

measurements of arrests. In each
case the prevalence of arrest was used, where 1 = arrested and 0
= not arrested in the
respective year (2007–2010). The six forms of arrest include
marijuana, hard drugs
(heroin, cocaine, hallucinogens, other opiates, amphetamines,
barbiturates, and syn-
thetic drugs), homicide, robbery, assault, and weapon offenses.
Prevalence was used
instead of frequency of arrest due to the fact that it is extremely
rare that an individual
would be arrested twice in the same fiscal year for a federal
offense.
Independent variables in the current study include age, sex,
race, citizenship status,
and marital status.
The arrestee’s sex is measured with a dichotomous variable that
is coded B1^ if the
offender is male and B0^ if the offender is female. Ethnicity of
the arrestee is broken
down into three categories: White/White Hispanic, Black/Black
Hispanic, and Other.
Ethnicity is broken into three dummy coded variables where 1 =
being a member of
that ethnic category and 0 = non-membership in that category.
In each model White/
White Hispanic was used as the reference category because it is
the largest category.
This predictor variable was coded using the same ethnicity
categories provided in FJSP
datasets, the source of information used in this analysis. As is
common in many
datasets, Hispanic defendants in the FJSP research series are
categorized as either

white or black. The lack of ethnicity and citizenship
information in criminal justice
datasets is a significant handicap to researchers examining the
interaction between
citizenship status and race/ethnicity.
Citizenship status is broken into three dummy coded variables:
(1) U.S. citizen, (2)
Non-citizen, and (3) Unknown status. For each citizenship
status variable, 1 = being a
member of that citizenship category and 0 = non-membership in
that category. For the
purpose of this study, U.S. citizens include individuals born in
the U.S.; individuals
who were born outside the U.S., but who have at least one
parent who is a U.S. citizen;
and individuals who were born alien but who have lawfully
become citizens of the
United States (i.e., Bnaturalized citizens^). Non-citizens are
individuals who are legal
(resident) aliens, unauthorized immigrants or individuals
without U.S. citizenship
476 Am J Crim Just (2017) 42:469–488
whose immigration status is unknown. An unauthorized
immigrant is a person who
resides in the United States but who is not a U.S. citizen, has
not been admitted for
permanent residence, and is not in a set of specific authorized
temporary statuses
permitting longer-term residence and work (see Passel et al.,
2004).

In each model U.S. citizenshi p was used as the reference
category because it is
the largest category. Descriptive analysis revealed that
approximately 3178 cases
(9.1 %) of total cases were missing citizenship status. Rather
than excluding those
cases it was decided to recode them as unknown in order to
identify possible
patterns in the missing values and to determine if those patterns
were consistent
with or different from other categories. One author of this study
has 22 years of
personal experience as a federal criminal investigator and
supervisory special
agent. Based on that experience, the following are possible
explanations for
missing demographic information in the PTS database (source
of information for
FJSP datasets used in this analysis). Reasons include the
inaccurate completion of
investigative reports due to human error and a lack of quality
review of those
reports by supervisory personnel. Additionally, the U.S.
Department of Justice
Office of the Inspector General (2004) determined that the
USMS (proprietor of
the PTS database) lacked proper internal controls to identify
and correct erroneous
or missing information contained within the computer database.
Marital status is also broken into three dummy variables, (1)
married, (2)
Unmarried (including divorced, single, and widowed
individuals), and (3) un-
known marital status. Like other dummy coded variables in this
study, 1 = being a

member of that marital category and 0 = non-membership in that
category. In each
model Unmarried was used as the reference category because i t
is the largest
category. Descriptive analysis revealed that approximately
15,166 cases (43.5 %)
of total cases were missing marital status. Rather than excluding
those cases it was
decided to recode them as unknown in order to identify possible
patterns in the
missing values and to determine if those patterns were
consistent with or different
from other categories. Possible explanations for the missing
values are discussed
above. Age, the final independent variable, was measured as age
in years, at the
time that the individual was arrested. Prior to any analysis
being run, these
variables were checked for collinearity, and none was found.
VIF scores ranged
from 1.023 (Tolerance = .977) to 1.415 (Tolerance = .707).
Analytic Strategy
Logistic regression was chosen to analyze the preceding
research questions, because it
is appropriate for use when the dependent variable or variables
(in this case the
prevalence of arrest for each type of offense) are dichotomous,
and it is appropriate
with all types of independent variables (Menard, 2010). Model
statistical significance
will be determined using the p-value associated with the model
chi-squared statistic,
and the model substantive significance will be determined using
the likelihood ratio R2,

also known as McFadden R2 or R2L. This measure of model
substantive significance
was chosen because it is conceptually the closest to R2 in OLS
regression, in that it
reflects the proportional reduction in the quantity actually being
minimized (Menard,
2010). Predictor statistical significance will be determined
using p-values computed
Am J Crim Just (2017) 42:469–488 477
from the Wald statistic, while predictor substantive significance
will be determined
using fully standardized regression coefficients. These
coefficients have the same
interpretation in logistic regression as in ordinary least squares
regression: A one
standard deviation change in the predictor is associated with a
b* standard deviation
change in the outcome, where b* is the fully standardized
regression coefficient. For a
full description of how these coefficients are calculated, see
Menard, 2010. While it is
the fully standardized regression coefficients that will be
interpreted by the authors,
odds ratios have also been inserted into the tables, for r eaders
who prefer that measure
of predictor substantive significance. Table 1 illustrates the
descriptive statistics for the
variables in the current study.
Results
Table 2 illustrates the results of the logistic regression arrest

models, for each offense
type. On this table we can see that the federal homicide arrest
model is statistically
(p = .000) and substantively (R2L=.276) significant.
Accordingly, the model explains
27.6 % of the variation between federal homicide arrests and
federal arrests for other
offenses. According to Wald statistics, individuals who are
disproportionately arrested
for a federal homicide offense are more likely to be male (p =
.002), White/White
Hispanic versus Black or Black/Hispanic (p = .016), a member
of an Bother^ racial
Table 1 Descriptive statistics
N Mean Standard deviation
Dependent variables
Homicide Arrests 34829 .0088 .09362
Assault Arrests 34829 .0313 .17412
Robbery Arrests 34829 .0146 .11989
Marijuana Arrests 34829 .5671 .49548
Hard Drug Arrests 34829 .2804 .44919
Weapons Arrests 34829 .0978 .29704
Independent variables
Age 34099 31.36 10.412

Sex 34828 .8410 .36566
White/White Hispanic 34828 .8984 .30207
Black/ Black Hispanic 34828 .0596 .23671
Other Race 34828 .0420 .20054
Married 34829 .2545 .43557
Unmarried 34829 .3101 .46254
Unknown Marriage 34829 .4354 .49582
US Citizen 34829 .5472 .49778
Non-Citizen 34829 .3616 .48046
Unknown Citizen Status 34829 .0912 .28796
478 Am J Crim Just (2017) 42:469–488
category (p = .000), a U.S. citizen versus a non-citizen (p =
.000), and/or a U.S. citizen
versus a member of an unknown citizen classification (p =
.000). Examination of the
standardized coefficients reveals that being a member of an
Bother^ or unknown race is
the strongest predictor of federal homicide arrests (b*M = .198)
followed by non-citizen
status (b*M = −.175), unknown citizenship status (b*M =
−.139), race (White/White
Hispanic versus Black or Black/Hispanic; b*M = −.111), and
finally by gender

(b*M = .058). Note that the typical cutoff for substantive
significance is a standardized
regression coefficient of .100 or higher. Using that standard,
gender (being male) is not
substantively significant, while all other statistically significant
predictors are.
Table 2 also shows that the model for federal assault arrests is
statistically (p = .000)
and substantively (R2L= .221) significant. Accordingly, it
explains 22.1 % of the
variation between federal arrests for assault and federal arrests
for other offenses. The
statistical significance of the predictors indicates that
individuals who were dispropor-
tionately arrested for federal assault, were more likely to be
male (p = .010), Black or
Black/Hispanic (p = .001), a member of an Bother^ racial
category (p = .000), a
member of an unknown marriage status category (p = .000), a
U.S. citizen versus a
non-citizen (p = .000), and/or a U.S. citizen versus a member of
an unknown citizen
classification (p = .000). Examination of the standardized
coefficients reveals that being
a member of an Bother^ or unknown race is the strongest
predictor of federal assault
arrests (b*M = .305) followed by citizenship status (non-citizen,
b*M = −.210 and
unknown citizenship, b*M = −.138), having an unknown marital
status (b*M = .070),
being Black/Black Hispanic (b*M = .049), and finally by gender
(b*M = .043). As
previously noted, the typical cutoff for substantive significance
is a standardized
regression coefficient of .100 or higher. Accordingly, the

predictors of gender (being
male), being Black or Black/Hispanic and having an unknown
marriage status while
statistically significant are not substantively significant.
The federal robbery arrest model is also statistically significant
(p = .000), but not
substantively significant (R2L= .008). The model only explains
.8 % of the variation in
the dependent variable. Federal robbery arrests have a
statistically significant relation-
ship with age (being older; p = .008), being male (p = .000),
being Black or Black/
Hispanic (p = .000), being a member of an Bother^ racial
category (p = .000), being
unmarried (versus being married or having an unknown marital
status (p = .000 for
both comparisons), and/or with being a U.S. citizen versus a
non-citizen (p = .000) or
being in an unknown citizen classification (p = .000).
Examination of the standardized
coefficients reveals that citizenship status is the strongest
predictor of federal robbery
arrests (non-citizen, b*M = −.103 and unknown citizenship
status, b*M = -.054),
followed by gender (b*M = .036), being unmarried versus
married (b*M = −.028),
being Black/Black Hispanic (b*M = .027), being a member of
an Bother^ or unknown
race (b*M = .019), being unmarried versus having an unknown
marital status
(b*M = −.016), and finally age (b*M = .013). Being a U.S.
citizen (versus being a
non-citizen) is the only predictor that is both statistically and
substantively significant.

Table 2 illustrates that the model for federal marijuana arrests is
statistically
(p = .000) significant and explains 7.8 % of variation in the
dependent variable
(R2L=.078). Federal marijuana arrests have a statistically
significant relationship with
age (being younger; p = .000), being female (p = .000), being
White/White Hispanic
versus Black or Black/Hispanic (p = .000) or being a member of
an Bother^ racial
Am J Crim Just (2017) 42:469–488 479
Table 2 Logistic regression arrest models
Dependent
Variable
Model
Statistics
Independent
Variables
Unstandardized
Coefficients (b)
Standardized
Coefficients (b*)
Significance
(Wald Statistic)
Federal Homicide

Arrests
R2L=.276 Age .010 .028 .087
p = .000 Male .584 .058 .002
Black/Black Hispanic -1.728 -.111 .016
Other Race 3.615 .198 .000
Unknown Marriage -.205 -.028 .142
Married .156 .019 .396
Non-Citizen -1.334 -.175 .000
Unknown Citizenship -1.770 -.139 .000
Federal Assault
Arrests
R2L= .221 Age -.004 -.020 .266
p = .000 Male .245 .043 .010
Black/Black Hispanic .443 .049 .001
Other Race 3.190 .305 .000
Unknown Marriage .297 .070 .000
Married -.121 -.025 .257
Non-Citizen -.915 -.210 .000

Federal Robbery
Arrests
R2L= .008 Age .011 .013 .008
p = .000 Male .890 .036 .000
Black/Black Hispanic 1.006 .027 .000
Other Race .829 .019 .000
Married -.583 -.028 .000
Non-Citizen -1.910 -.103 .000
Federal Marijuana
Arrests
R2L= .078 Age -.020 -.094 .000
p = .000 Male -.188 -.031 .000
Black/Black Hispanic -1.460 -.156 .000
Other Race -1.382 -.125 .000
Unknown Marriage .531 .119 .000
Married .157 .031 .000
Non-Citizen .686 .149 .000

Unknown Citizenship .630 .082 .000
Federal Hard
Drug Arrests
R2L= .037 Age .021 .093 .000
p = .000 Male -.380 -.059 .000
Other Race -.933 -.080 .000
480 Am J Crim Just (2017) 42:469–488
category (p = .000), having an unknown marriage status (p =
.000), being married
(p = .000), being a non-citizen versus a U.S. citizen (p = .000),
and being an unknown
citizen classification versus a U.S. citizen (p = .000).
Examination of the standardized
coefficients reveals that being White/White Hispanic versus
Black/Black Hispanic is
the strongest predictor of federal marijuana arrests (b*M =
−.156), followed by being a
non-citizen (b*M = .149), being White/White Hispanic versus a
member of an Bother^
or unknown race (b*M = −.125), having an unknown marital
status (b*M = .119), being
younger (b*M = −.094), having an unknown citizenship status
(b*M = .082), and finally

gender (being female, b*M = −.031) and being married (b*M =
.031). Age, gender
(being female), being married and having an unknown
citizenship status are not
substantively significant, while all other statistically significant
predictors are.
As with other models, the model for federal hard drug arrests is
statistically (p = .000)
and substantively (R2L=.037) significant. Accordingly, the
model explains 3.7 % of the
variation between federal hard drug arrests and federal arrests
for other offenses. Federal
hard drug arrests have a statistically significant relationship
with age (being older;
p = .000), being female (p = .000), being Black or
Black/Hispanic (p = .000), being
White/White Hispanic versus being a member of an Bother^
racial category (p = .000),
being unmarried versus having an unknown marriage status (p =
.000), and being a U.S.
citizen versus being a non-citizen (p = .000). Examination of
the standardized coeffi-
cients reveals that being unmarried versus having an unknown
marital status is the
strongest predictor of federal hard drug arrests (b*M = −.098),
followed by age
(b*M = −.093), not being a member of an Bother^ or unknown
race (b*M = −.080),
being Black/Black Hispanic (b*M = .075), being female (b*M =
−.059) and finally being
a U.S. Citizen versus a non-citizen (b*M = −.044), however,
none of the predictors
reached the standard cutoff for substantive significance (b*M ≥
.100).

According to Table 2, the federal weapons arrest model is
statistically significant
(p = .000) and substantively significant (R2L = .075). The
model explains 7.5 % of the
variation in the dependent variable. Federal weapons arrests
have a statistically
Table 2 (continued)
Dependent
Variable
Model
Statistics
Independent
Variables
Unstandardized
Coefficients (b)
Standardized
Coefficients (b*)
Significance
(Wald Statistic)
Married .022 .004 .482
Non-Citizen -.214 -.044 .000
Unknown Citizenship .046 .006 .352
Federal Weapons
Arrests

R2L= .075 Age .001 .003 .450
p = .000 Male 1.709 .162 .000
Other Race -.270 -.014 .000
Married -.306 -.034 .000
Non-Citizen -.964 -.120 .000
Am J Crim Just (2017) 42:469–488 481
significant relationship with being male (p = .000), being Black
or Black/Hispanic
(p = .000), being White/White Hispanic versus being a member
of an Bother^ racial
category (p = .000), being unmarried versus being married (p =
.000) or having an
unknown marriage status (p = .000), and with being a U.S.
citizen versus being a non-
citizen (p = .000) or being an unknown citizen classification (p
= .000). Examination of
the standardized coefficients reveals that gender (being male) is
the strongest predictor
of federal weapon offenses (b*M = .162), followed by being a
U.S. citizen (versus being
a non-citizen, b*M = −.120, and being of an unknown
citizenship status, b*M = −.114),

being Black/Black Hispanic (b*M = .043) being married (versus
being in an unknown
marital category, b*M = −.043, or being married, b*M = −.034),
and finally, being
White/White Hispanic as opposed to being a member of an
Bother^ or unknown race
(b*M = −.014). Only the predictors of gender (being male),
being a U.S. citizen are both
statistically and substantively significant.
Discussion
This study analyzed the impact of citizenship status on
disproportionate federal arrests
for six violent and narcotic-related offenses (homicide, assault,
robbery, marijuana, hard
drug and weapons) along the U.S./Mexico border, in the interest
of answering two
specific research questions. The answers to those questions
require some attention here.
Recall that the first research question asked about the
characteristics of individuals who
were disproportionately arrested for each of the federal
offenses. Table 3 contains a
summary of the multivariate findings that are both statistically
and substantively
significant. From this table, we can see that individuals arrested
for a federal homicide
offense are disproportionately individuals whose ethnicity is
either White/White
Hispanic or Bother^, and who are U.S. citizens. Individuals
arrested for a federal assault
Table 3 Summary of multivariate results
Homicide

Arrests
Assault
Arrests
Robbery
Arrests
Marijuana
Arrests
Hard Drug
Arrests
Weapons
Arrests
Age
Male +
Black/Black
Hispanic
− −
Other Race + + −
Unknown
Marriage
+
Married
Non-Citizen − − − + −

Unknown
Citizenship
− − −
A positive sign (+) indicates a statistically and substantively
significant positive relationship, while a negative
sign (−) indicates a significant negative relationship
482 Am J Crim Just (2017) 42:469–488
are disproportionately U.S. citizens and individuals whose
ethnicity is of an unknown
classification. Individuals who are arrested for a federal level
robbery offense, as
opposed to some other federal offense, are disproportionately
U.S. citizens.
Individuals arrested on federal marijuana charges are
disproportionately White/White
Hispanic, have an unknown marital status, and are non-citizens.
None of the examined
independent variables had a statistically and substantively
significant impact on dis-
proportionate federal arrests for hard drug use and therefore,
our research does not lend
any insight into the characteristics of these offenders. Finally,
individuals arrested on
federal weapons charges are disproportionately male and are
U.S. citizens.
Though not substantively significant, one interesting findings
from our multivariate
analyses is that females were statistically significantly,

disproportionately, more likely
than males to be arrested for marijuana and hard drug offenses.
This is consistent with
previous research that shows that women are more likely to be
arrested for drug and
property related offenses rather than violent crime (Chesney-
Lind, 1997; Bloom et al.,
2004). According to the Bureau of Justice statistics, females
accounted for 15 % of all
DEA drug arrests and 20 % of all methamphetamine arrests in
2010 (Motivans, 2010).
Therefore, the results from this study add further support to the
differences in arrest by
type of crime and gender.
The second research question specifically asked if noncitizens
were disproportion-
ately more likely than U.S. citizens to be arrested for each of
the six federal offenses.
With only one exception, the answer to these research questions
was no – noncitizens
were not disproportionately more likely to be arrested than U.S.
citizens in the federal
districts that line the U.S./Mexico border. Recall that this
region contains the largest
concentration of Hispanic citizens in the United States (Ennis et
al., 2011), and an
estimated 4.7 million illegal immigrants (Passel & Cohn, 2011).
The only federal
crime where noncitizens were disproportionately more likely to
be arrested than were
U.S. citizens was for marijuana offenses. Overall, these findings
are consistent with
recent research that shows that noncitizens are less likely to be
arrested than U.S.
citizens for violent and drug-related offenses. The only

exception, marijuana contra-
dicts recent studies that suggest that U.S. citizens are more
likely to be arrested for
drug related offenses than are noncitizens (Becker et al., 2013;
Hagan & Palloni,
1999; Kposowa et al., 2009). Marcelli (2004) did find that
noncitizens who were
arrested were more likely to be apprehended for a drug-related
offense than any other
type of crime.
Cultural, opportunity structure and social disorganization are
three traditional theo-
retical frameworks that are used to explain immigrant
criminality. These theories all
generally postulate that immigration promotes criminal activity.
More recently, the
immigration revitalization perspective argues that protective
factors of immigrant
communities actually decrease (rather than increase) the
likelihood of criminal activity.
While this research did not directly test any of the theories, they
did offer a perspective
for why one might expect to see differences in arrest rates
relative to citizenship status.
Overall, this research showed that with the exception of federal
marijuana arrests, that
noncitizens were disproportionately less likely to be arrested for
violent and narcotic-
related federal offenses than were U.S. citizens. Results of this
study tend to support the
immigration revitalization perspective rather than traditional
criminological theories
(i.e., cultural, opportunity structure and social disorganization)
that suggest that non-
citizens are more likely than U.S. citizens to be arrested.

Am J Crim Just (2017) 42:469–488 483
Limitations
It is important to acknowledge some limitations to the present
study. One limitation of
this research is that the utilization of citizenship status in the
assessment of immigrant
criminality has some important drawbacks. The primary issue is
that citizenship data
cannot distinguish between noncitizens who are in the U.S.
legally (resident aliens) and
those who are unauthorized. It is, of course, the unauthorized
noncitizens that are the
focus of media attention and who members of the general public
appear to be
concerned with in terms of criminality, among other things.
This limitation is not
unique to this research (Heckathorn, 2006). Despite the inability
to distinguish between
authorized and unauthorized noncitizens, researchers often use
citizenship information
when examining immigrant criminality. This is due to the
inherent difficulty in gaining
information from individuals who are in the United States
illegally. Still, the lack of
information regarding immigrant status continues to be a
significant impediment to
researchers studying immigrant criminality.
A second limitation of the current study was that the dataset
used in this research
(the FJSP research series) like many formal crime data sources

(e.g., Uniform Crime
Report) failed to provide an ethnic breakdown of defendants. As
is common in many
datasets, Hispanic defendants were categorized as either white
or black. The lack of
ethnicity in criminal justice datasets continues to impede
research efforts examining the
link between ethnicity, race and crime. Another limitation of
this data set is the use of
arrests as an indication of criminal behavior. As has been amply
documented elsewhere
(for example, O’Brien, 1985; Pollock et al., 2015), arrest data
reflect not only illegal
behavior but also policies with regard to enforcement and the
recording of police
actions, and are less consistent and reliable indicators of illegal
behavior and victim-
ization data. While the use of arrestees does allow us to
examine whether arrests for
different types of crime are disproportionately concentrated
within immigrant or non-
immigrant populations, it is not possible from these data to
compute rates of illegal
behavior relative to the general population of immigrants and
non-immigrants, partic-
ularly because estimates of the numbers of the immigrant
(including but not limited to
illegal immigrant) vary widely, by as much as 10 %, or between
10.7 and 11.7 million
in 2010 (Passel & Cohn, 2011; Warren & Warren, 2013).
Stated differently, it is virtually impossible to get information
on actual criminal
behavior from immigrants in general and even more so from
illegal immigrants. This is
because illegal immigrants are, understandably, difficult to

locate and interview regard-
ing their criminal behavior or their victimization. Arrest records
are admittedly flawed
indicators of criminal behavior, for the above stated reasons,
but they are the best
measure presently available for examining the current issue on a
large scale. In
addition, we know from previous research (see Pollock, 2014),
that there is a statisti-
cally significant, positive, correlation between criminal
behavior and arrest. Therefore,
some knowledge can be gained regarding criminal behavior
through arrest records,
though again, self-report or victimization data would be
preferable.
Despite the above limitations, the current study has some
important implications for
policy, as well as future research. The goal of the current study
was to contribute to the
body of research providing a non-discriminative understanding
of both crime and
immigration. Overall, the results of the current research
challenge the stereotypical
linkage of non-citizens to crime. This research like other recent
studies investigating the
484 Am J Crim Just (2017) 42:469–488
association between immigration and crime found that
noncitizens were not dispropor-
tionately arrested for federal crime on the U.S. / Mexico border.
This is important
because it challenges the claims of politicians and media

sources that promote the fear
of immigrants in order to further their own agendas. The myth
of the criminal
immigrant is perhaps one of the single most controversial
factors contributing to
America’s present day anti-immigrant fervor. Results of the
current study and other
research provide hard evidence challenging the mythology of
the criminal immigrant
and will hopefully contribute to a more coherent and meaningful
national dialogue on
immigration policy.
Additional research is necessary to explore the intricacies of the
relationship be-
tween citizenship and crime in the United States. Investigation
into the consistency of
the impact of citizenship on federal arrests over time (i.e.,
before and after President
Calderon’s presidency) was not addressed in the current study.
Second, the findings of
this study were confined to the federal arrest process. Future
studies are needed to
determine whether similar results hold true for state agencies.
Third, inter-district
variation was not explored in the current study. Investigating
differences in arrest
predictors between federal districts has not been done
previously and would certainly
contribute to the body of research exploring the role of
citizenship and arrest. Finally,
examination of the role of citizenship status as a predictor of
federal arrests for other
types of offenses (e.g., property) is also essential to gain a more
complete picture of the
interaction between citizenship and crime.

Acknowledgments The authors would like to thank the Inter-
university Consortium for Political and Social
Research (ICPSR) for allowing the use of the data in this study.
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immigration, and homeland security. Westport:
Praeger Security International.
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examination of the correlates of police contact.
Crime & Delinquency, 60(8), 1183–1208.
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officially recorded arrests. Journal of Criminal Justice, 43, 69–
79.
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United States and Mexico with a focus on the
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Research Institute (ASU), United States
Mexico Policy Analysis Tool (USMexPAT) website:
http://usmexpat.com/research/background-reports/.
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immigrant criminality and the paradox of assimilation:
Incarceration rates among native and foreign-born men.
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Immigration Law Foundation.
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increased immigration behind the drop in crime?
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Deborah A. Sibila is an Assistant Professor of Criminal Justice

at Stephen F. Austin State University in
Nacogdoches, Texas. She received her B.A. in Law
Enforcement/Police Science from Sam Houston State
University (SHSU), her MPA from Jacksonville State University
and her Ph.D. from SHSU. Her current
research focus includes female and elderly offending, immigrant
criminality and drug policy.
Wendi Pollock is an assistant professor of Criminal Justice at
Texas A&M University – Corpus Christi. She
received her B.S. and M.S. in criminal justice from Sul Ross
State University, and her Ph.D. in criminal justice
from Sam Houston State University. Her current research focus
includes the correlates of disproportionate
police contact both longitudinally and across generations,
perceptions of police fairness, the impact of criminal
justice system policies that center on arrest, quantitative
methods, and methodological concerns in self-
reported data.
Scott Menard is a retired Professor of Criminal Justice (Sam
Houston State University) and a Research
Associate in the Institute of Behavioral Science at the
University of Colorado, Boulder. He received his Ph.D.
in Sociology from the University of Colorado, Boulder. His
publications include work in statistics, particularly
logistic regression analysis and longitudinal research, plus
criminological theory testing and research on crime,
delinquency, and victimization intergenerationally and over the
life course.
488 Am J Crim Just (2017) 42:469–488
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copyright owner. Further
reproduction prohibited without
permission.
Citizenship...AbstractHistory of Immigration and Crime Theory
and ResearchThe Southwest BorderThe Federal Criminal Justice
System and the Southwest BorderCurrent
StudyDataVariablesAnalytic
StrategyResultsDiscussionLimitationsReferences
Reproduced with permission of the copyright owner. Further
reproduction prohibited without permission.
United States-Mexico: The Convergence of Public Policy Views
in the Post-9/11 World
Valeriano, Brandon;Powers, Matthew
Policy Studies Journal; Nov 2010; 38, 4; ProQuest
pg. 745

War or pseudo-war?
Miranda, Joseph
Social Justice; Summer 1998; 25, 2; ProQuest Central

pg. 65

6/5/2021 Illicit Drug Trade
https://myclassroom.apus.edu/d2l/le/enhancedSequenceViewer/3
4763?url=https%3A%2F%2Ff54cbe36-23a9-4505-85fe-
e251f80ec34d.sequences.a… 1/1
Since the early 2000s, Mexico has been “in the midst of a ba�le
between warring organized crime fac�ons”

(Simser, 2011, p. 267) commonly referred to as cartels that
exploit corrup�on, subversion, penetra�on, extreme
violence, assassina�ons, kidnappings, and other violent
methods intended to promote their interests.
Moreover, cartels have been warring not only with the
government but also among themselves, striving to
establish dominance and control over key plazas that are portals
for the smuggling of illicit drugs into the
United States (Simser, 2011). Some researchers and
policymakers even claim that Mexican cartels should be
defined as insurgent groups that have a real chance of seizing
power in the country should their further
evolu�onary pace remain on the exis�ng track (Blaine, 2012).
This opinion complies with a similar viewpoint
accredited to the Drug Enforcement Administra�on that there
has occurred “a transi�on from the gangsterism
of tradi�onal narco hitmen to paramilitary terrorism with
guerilla tac�cs” (Turbiville, 2010, p. 123). Therefore,
this evolu�on of cartels calls for the development and
implementa�on of new an�-drug measures and combat
strategies.
Although the Mexican government, especially under the rule of
President Calderon, has a�empted to
implement new amendments since 2006, they have proved to be
only par�ally successful (Turbiville, 2010).
Understandably, violence is an integral part of the illicit drug
trade irrespec�ve of the par�cular drug and
country, yet the level of violence in Mexico is truly alarming
(Bei�el, 2012). As of 2006, there were four main
cartels: (a) the Tijuana/Arellano Felix organiza�on, (b) the
Gulf cartel, (c) the Sinaloa cartel, and (d) the
Juarez/Vicente Carillo Fuentes organiza�on (Bei�el, 2012).
The government’s steps, in par�cular, the
involvement of the military in the fight with cartels, enhanced
intelligence gathering, coopera�on with the

United States, and other measures, have resulted in extreme
fragmenta�on of the organiza�ons (Bei�el, 2012).
Hence, as of 2015, there are now nine cartels along with the
four previously men�oned; the five new cartels
are (a) Los Zetas, (b) Beltran Leyva Organiza�on, (c) La
Familia Michoacana, (d) Knights Templar, and (e) Cartel
Jalisco-New Genera�on (Bei�el, 2015). These cartels have
managed to func�on with li�le problems despite the
fact the government has either captured or killed the kingpins of
all of these cartels, for instance, the capture of
Joaquin “El Chapo” Guzman from the Sinaloa in 2014 and the
arrest of Hector Beltran Leyva from the Beltran
Leyva Organiza�on in 2014 (Bei�el, 2015). Furthermore, the
violence remains an actual problem, irrespec�ve
of some successes in bringing down the homicide rate as cartels
have intensified ac�vi�es related to
kidnappings, extor�ons, and threats (Bei�el, 2015).
6/5/2021 How Mexican Government Handle Situation
How Mexican Government Handle
Situation
The success of the government has been undermined by a failure
to disrupt opera�ons of cartels through
captures of the kingpins and the recent escape of Guzman on
July 11, 2015 (Bei�el, 2015). There are
supposi�ons that the Sinaloa cartel is vying to seize dominance
in Mexico and unite other cartels. On the one

hand, it will reduce the level of inter-cartel violence, but on the
other hand, such development of the situa�on
would pose a serious challenge to the government that already
struggles to devise a solu�on under the rule of
recently elected President Enrique Pena Nieto (Bei�el, 2015).
Hence, it is to be seen whether the Mexican
government can handle the increased power of cartels and
effec�vely prevent their further spread.
All in all, the U.S. government is extremely worried about the
Mexican situa�on because of the increasing
violence that can spill over into the United States, which
happens to be the target des�na�on of illicit drug
shipments. Therefore, it is frequently recommended for the U.S.
government to cooperate with the Mexican
government with access to efficiently figh�ng powerful drug
cartels that pose a significant threat to the United
States’ na�onal security and overall well-being of society.
6/5/2021 References
References
Beittel, J. S. (2012, August 3). Mexico’s drug trafficking
organizations: Source and scope of the rising violence.
Congressional Research Service.
Beittel, J. S. (2015, July 22). Mexico: Organized crime and drug
trafficking organizations. Congressional Research

Service.
Blaine, B. B. (2012, January). Mexican drug cartels. Marine
Corps Gazette, 96(1), 40-42. https://www.mca-
marines.org/gazette
Simser, J. (2011). Plata o plomo: Penetration, the purchase of
power and the Mexican drug cartels. Journal of
Money Laundering Control, 14(3), 266–278.
http://dx.doi.org/10.1108/13685201111147568
Turbiville, G. H. (2010). Firefights, raids, and assassinations:
Tactical forms of cartel violence and their
underpinnings. Small Wars & Insurgencies, 21(1), 123-
144. http://dx.doi.org/10.1080/09592310903561577

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