Available via license: CC BY-NC 4.0
Content may be subject to copyright.
https://doi.org/10.1177/2053168017712885
Research and Politics
April-June 2017: 1 –7
© The Author(s) 2017
Reprints and permissions:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/2053168017712885
journals.sagepub.com/home/rap
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons
Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial
use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and
Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
“I suppose it is tempting, if the only tool you have is a
hammer, to treat everything as if it were a nail.”
Abraham Maslow, The Psychology of Science:
A Reconnaissance (1966)
“Soldierin’ and policin’ – they ain’t the same thing.”
Major Howard “Bunny” Colvin, The Wire
Season 3, Episode 10 (2014)
Introduction
The summer of 2014 saw protracted protests to the non-
response associated with the killing of 18-year-old Michael
Brown. By the second day of protests, police officers
showed up in armored vehicles wearing camouflage, bul-
let-proof vests, and gas masks brandishing shotguns and
M4 rifles (Chokshi, 2014). That militarized response led to
a wave of criticism from observers including former mili-
tary personnel and politicians from both sides of the aisle.
In response, the federal government launched an investiga-
tion that ultimately resulted in Executive Order 13688
(EO). The EO sought to regulate the Department of
Defense 1033 program, which makes surplus military
equipment available to state, local, and tribal law enforce-
ment agencies (LEAs) at no cost. The EO banned LEAs
from acquiring certain equipment, and restricted them
from acquiring others.1 It also called for transparency and
training regarding the materials received. Some feared the
demilitarized police departments would no longer be able
to keep up with drug dealers, rioters, and terrorists. US
Representative John Ratcliffe introduced the Protecting
Lives Using Surplus Equipment Act to the House of
Representatives that would nullify all aspects of the EO.2
Militarization and police violence:
The case of the 1033 program
Casey Delehanty1, Jack Mewhirter2, Ryan Welch3
and Jason Wilks4*
Abstract
Does increased militarization of law enforcement agencies (LEAs) lead to an increase in violent behavior among officers?
We theorize that the receipt of military equipment increases multiple dimensions of LEA militarization (material, cultural,
organizational, and operational) and that such increases lead to more violent behavior. The US Department of Defense
1033 program makes excess military equipment, including weapons and vehicles, available to local LEAs. The variation in
the amount of transferred equipment allows us to probe the relationship between military transfers and police violence.
We estimate a series of regressions that test the effect of 1033 transfers on three dependent variables meant to capture
police violence: the number of civilian casualties; the change in the number of civilian casualties; and the number of dogs
killed by police. We find a positive and statistically significant relationship between 1033 transfers and fatalities from
officer-involved shootings across all models.
Keywords
Militarization, police, shootings
(*The names of the authors are listed in alphabetical order)
1 Department of Social Sciences, Gardner-Webb University, Boiling
Springs, NC, USA
2
Department of Political Science, University of Cincinnati, Cincinnati,
OH, USA
3 Department of Psychology, Stanford, CA, USA
4
Kennedy School of Government, Harvard University, Cambridge,
MA, USA
Corresponding author:
Casey Delehanty, Department of Social Sciences, Gardner-Webb
University, 110 South Main Street, P.O. Box 997, Boiling Springs, NC
28017, USA.
Email: cpdelehanty@gmail.com Twitter: @caseydelehanty
712885RAP0010.1177/2053168017712885Research & PoliticsDelehanty et al.
research-article2017
Research Article
2 Research and Politics
In an interview, he said “It would be one thing if there was
some evidence that showed state and local law enforce-
ment had abuse [sic] or misused the equipment, and then
caused undue or unnecessary harm to American citizens.
That isn’t the case” (Jennings, 2016). This paper provides
the first attempt to analyze whether and to what extent
military transfers have increased the propensity by which
LEAs cause “undue or unnecessary harm.”
Drawing from Kraska (2007), we argue that increasing
LEA access to military equipment will lead to higher levels
of aggregate LEA violence. The effect occurs because the
equipment leads to a culture of militarization over four
dimensions: material; cultural; organizational; and opera-
tional. As militarization seeps into their cultures, LEAs rely
more on violence to solve problems. The mechanism mir-
rors psychology’s classic “Law of the Instrument,” whereby
access to a certain tool increases the probability that the
tool is used for problems when other tools may be more
appropriate (Maslow, 1966), including access to weapons
increasing violent responses (e.g. Anderson et al., 1998;
Berkowitz and LePage, 1967).
We evaluate this proposition using county-level data on
police killings in four US states: Connecticut, Maine,
Nevada, and New Hampshire (Burghart, 2015); and the
data on 1033 program receipts (https://github.com/wash-
ingtonpost/data-1033-program). Estimating a series of
regressions, we find that 1033 receipts are associated with
both an increase in the number of observed police killings
in a given year as well as the change in the number of police
killings from year to year, controlling for a battery of pos-
sible confounding variables including county wealth, racial
makeup, civilian drug use, and violent crime. Given that
establishing a causal effect between 1033 receipts is poten-
tially problematic due to concerns of endogeneity, we re-
estimate our regressions using an alternative dependent
variable independent of the process by which LEAs request
and receive military goods: the number of dogs killed by
LEAs. We find 1033 receipts are associated with an increase
in the number of civilian dogs killed by police. Combined,
our analyses provide support for the argument that 1033
receipts lead to more LEA violence.
We organize the rest of the paper as follows. First, we
provide an argument that links police militarization and
police violence. Next, we briefly introduce the reader to the
1033 program and why it is appropriate for studying the
question at hand. Next, we describe the data and empirical
strategy. Then we present the results. Finally, we conclude
with some thoughts about how the research should influ-
ence policy and can be expanded in the future.
Militarization
Borrowing from Kraska (2007: 503), we define militariza-
tion as the embrace and implementation of an ideology that
stresses the use of force as the appropriate and efficacious
means to solve problems. Kraska (2007) provides four
dimensions of militarization: material; cultural; organiza-
tional; and operational. We contend these dimensions rein-
force one another so that an increase in one can lead to an
increase in others. More specifically, the military equip-
ment obtained from the 1033 program directly increases the
material dimension. With the new equipment, martial lan-
guage (cultural), martial arrangements such as elite units
(organizational), and willingness to engage in high-risk
situations (operational) increase (Balko, 2014). Military
equipment naturally increases military-style training for
said equipment. That training can increase the other dimen-
sions of militarization. One trainer’s quote illustrates well
the uptake of militarized culture: “Most of these guys just
like to play war; they get a rush out of search and destroy
missions instead of the bullshit they do normally” (Kraska,
2001, quoted in Balko, 2014: 212). But the trainees would
not have to settle for the normal “bullshit” for long. Many
LEAs began practicing SWAT raids on low-level offenders
as a way to train and then as a matter of normal policy
(Balko, 2014; Sanow, 2011). Officers running military
operations with military tools and military mindsets organ-
ized militarily will rely more on the tenets of militarization
(e.g. the use of force to solve problems) which should
increase the use of violence on average. Since 1997, LEAs
obtain much if not most of their military equipment from
the 1033 program.
1033 program and militarization
President Bill Clinton signed into law H.R. 3230 (National
Defense Authorization Act for Fiscal Year 1997). The bill
contains section 1033, which allows the Secretary of Defense
to sell or transfer excess military equipment to local LEAs.
Between 2006 and April of 2014 alone, the Department of
Defense transferred over $1.5 billion worth of equipment
including over 600 mine-resistant ambush-protected vehi-
cles, 79,288 assault rifles, 205 grenade launchers, 11,959
bayonets, 50 airplanes, 422 helicopters, and $3.6 million
worth of camouflage and other “deception equipment”
(Rezvani et al., 2014). Eighty percent of US counties received
transfers, and those transfers increased over time from 2006
to 2013 by 1414% (Radil et al., 2017). These variations
allow us to test the proposition that, all things being equal,
the receipt of higher levels of 1033 equipment will lead to
increased levels of violence from LEAs.
Data
Ultimately, the goal of this paper is to empirically assess
the relationship between 1033 transfers and police vio-
lence. To do so, we use a unique time-series cross-sectional
dataset, drawing from several sources. The dataset consists
of county level data for four states – Connecticut, Maine,
Nevada, and New Hampshire – from 2006–2014 (n = 455).
Delehanty et al. 3
Our primary analyses use two dependent variables in
two separate models: (1) the number of civilians killed by
LEAs in a given county for a given year; and (2) the
observed change in killings in a county between a given
year and the previous year. The first most directly tests the
outcome of interest. We also regress the change in killings
from the previous year on the independent variables in
order to somewhat address endogeneity issues. That is, one
could reasonably expect LEAs with high raw levels of kill-
ing to seek more 1033 transfers. However, it should be
harder (though not impossible) for LEAs to anticipate how
their need to use violence will change from year to year. On
top of that, we control for the average number of killings in
the county in the regression using the change in killings
dependent variable.
We constructed the variables using data from the Fatal
Encounters (Burghart, 2015) database, which, drawing
from other (incomplete) datasets, public record requests,
and crowd-sourced reports, provides a more comprehen-
sive list regarding police killings for selected states. When
constructing the dataset, only data for Connecticut, Maine,
Nevada, and New Hampshire were available, thus limiting
the sample to all counties within these states.3
The explanatory variable of interest measures the total
value of military surplus goods transferred to LEAs in a
given county in the previous year (logged US$). We believe
that use of a lagged measure somewhat addresses endoge-
neity concerns since operational, organizational, and cul-
tural shifts are expected to occur sometime after the
materials arrive, and training has completed. We used the
data from the 1033 dataset released by the Washington Post
(https://github.com/washingtonpost/data-1033-program),
which compiles raw data regarding 1033 transfers released
by the US Department of Defense Logistics Agency in
2014. From 2006–2014, nearly 88% of the counties in our
dataset received at least one 1033-transfer: the median
county received goods valued at roughly $50,000. Note that
while our data contains information from 2006–2014, our
use of a lagged independent variable eliminates the 2006
year from our empirical analysis (n = 390).
Figure 1 illustrates the relationship between 1033 trans-
fers and counties that experienced at least one killing in
Nevada in 2013.4 No LEA killings occurred in counties that
did not receive military equipment. While suggestive, we
next move to more rigorous statistical tests with controls to
increase the credibility of our claims.
We include several variables that we expect to simultane-
ously correlate with military expenditures and police vio-
lence in order to avoid biased estimates. Based on other
research we included median household income (e.g.
Mitchell and Wood, 1998; US Census Bureau, 2016),5 pop-
ulation (e.g. Jacobs, 1998; US Census Bureau, 2016), black
population (e.g. Ross, 2015; US Census Bureau, 2016), vio-
lent crime (e.g. Federal Bureau of Investigation, 2010;
Jacobs, 1998), and civilian drug use (Balko, 2014; Substance
Abuse and Mental Health Services Administration, 2016) as
controls.6 When using the number of observed killings as
the dependent variable we also include a lagged dependent
variable to control for autocorrelation (Beck and Katz,
1995). When the change in killings is used as the dependent
variables, we include the mean number of killings in that
county over the observed time period as a control. We pro-
vide descriptive statistics for all variables in Table A1 in the
Online Appendix.
Empirical analysis
In order to test the proposed relationship between 1033
receipts and our dependent variables, we estimate two sep-
arate regressions on an unbalanced time-series cross-sec-
tion data set from the years 2006 to 2014 with standard
errors clustered on county.7 When we estimate the expected
number of killings we utilize a negative binomial regres-
sion; when we estimate the change in police killings, we
use ordinary least squares regression. Prior to estimation,
we use the multiple imputation method recommended by
King and Wittenberg (2000) to avoid potential bias intro-
duced by dropping observations that contain missing data.
The extent to which each variable is imputed is shown in
Table A2 in the Online Appendix.
Results
The results, presented in Table 1, confirm our argument: the
receipt of more military equipment increases both the
expected number of civilians killed by police (β = 0.055; p
= 0.016) and the change in civilian deaths (β = 0.017; p =
0.082). Given the difficulty of interpreting the substantive
effect of a logged independent variable, we rely on the pre-
dicted value graph in Figures 2 and 3. As shown in Figure
2, receiving no military equipment corresponds with 0.287
expected civilian killings in a given county for a given year,
whereas receiving the maximum amount corresponds with
0.656 killings. In other words, moving from the minimum
to the maximum expenditure values, on average, increases
civilian deaths by roughly 129%. As seen in Figure 3, coun-
ties that received no military equipment can expect to kill
0.068 fewer civilians, relative to the previous year, whereas
those that received the maximum amount can expect to kill
0.188 more, holding all else constant.
Alternative dependent variable: dog
casualties
While we believe that civilian casualty dependent variables
provide the most direct test of our hypothesis, empirically
establishing a causal relationship between killings and mili-
tary transfers presents a challenge given the potential for
endogeneity. Specifically, if LEAs anticipate future conflict
with civilians (and they are correct) and thus seek more
4 Research and Politics
1033 transfers, then our estimates will be systematically
biased. To account for this, we utilize an alternative depend-
ent variable that should be independent of LEAs’
propensity to request and receive transfers: the number of
dogs killed by police in a county for each included year
(2006–2013). That is, we do not expect LEAs to consider
Figure 1. The relationship between 1033 transfers and law enforcement agency killings in Nevada counties in 2013. Map created in
ArcMap 10.4 (Esri, 2016). Darker green counties received more military equipment. Those counties with a bullseye experienced at
least one killing.
Delehanty et al. 5
the number of pets they will encounter when applying for
military equipment. These data are taken from the
Puppycide Database Project (2016), a crowdsourced data-
base that provides the first nationwide database to track
police shooting of animals.8
To test the relationship between lagged transfers and
dogs killed by police, we estimate a negative binomial
regression, including the same controls as the previous
regressions (as well as a lagged dependent variable).
Results, presented in Table 2, confirm that a positive rela-
tionship exists. Holding all else constant, police that
received the highest 1033 transfers kill dogs at an order of
magnitude higher rate than those with no transfers (0.161
compared with 0.009). Such findings strengthen our confi-
dence in the claim that military transfers are related to LEA
violence.
Conclusion
Political scientists possess theoretical and methodological
tools to weigh into today’s debates about police violence.
This study answers the call for evidence-based policy
Table 1. Full regression results.
Variables Civilian deaths Change in civilian deaths
Expenditures (lag) 0.055**
(0.023)
0.017*
(0.01)
Civilian deaths (lag) 0.073*
(0.04)
Civilian death (mean) −0.139*
(0.054)
Violent crime 0.023
(0.044)
0.001
(0.056)
Civilian drug-use −0.104
(0.094)
−0.06
(0.046)
Median income −0.910*
(0.549)
−0.006
(0.139)
Black population −0.040
(0.162)
−0.023
(0.071)
Population 0.872**
(0.339)
0.086
(0.132)
Constant −0.387
(5.59)
−0.092
(1.921)
Observations 390 390
Note: clustered standard errors in parentheses: ***p < 0.01; **p < 0.05;
*p < 0.1.
Figure 2. Expected number of killings over the range of the
explanatory variable with 90% confidence intervals. All other
variables held at their means.
Figure 3. Expected change in killings over the range of the
explanatory variable with 90% confidence intervals. All other
variables held at their means.
Table 2. Negative binomial regression results using dog
casualties as the dependent variable.
Variables Dog casualties
Expenditures (lag) 0.162*
(0.093)
Dog casualties (lag) 0.217*
(0.33)
Violent crime 0.043
(0.095)
Civilian drug-use 0.105
(0.337)
Median income −0.015
(1.659)
Black population 0.848
(0.643)
Population −0.361
(1.197)
Constant −8.488
(19.562)
Observations 389
Note: clustered standard errors in parentheses: *** p < 0.01; ** p < 0.05;
* p < 0.1.
6 Research and Politics
analysis by Representative Ratcliffe and others as they
continue to debate the merits of the 1033 program (Murtha,
2016). We acknowledge that the present analysis is rela-
tively preliminary. Due to notoriously unavailable data on
police violence against the public, we present what we
consider to be a best attempt at establishing the proposed
relationship between military transfers and violence.9
Further, while no research method offers full certainty of
a causal effect, we attempt to increase the plausibility of
the claim that 1033 transfers lead to more police violence.
We do so by measuring the transfers in the previous year,
as well as by leveraging three different dependent varia-
bles. While the first dependent variable – civilian killings
– represents the most direct measure to test the claim,
using the next two dependent variables – change in civil-
ian killings and dog killings – helped bypass endogeneity
concerns to an extent. As more social scientists take up
this sort of research, we expect replication and extension
of these results in different jurisdictions with different
methods.
As for policy, our results suggest that implementing the
EO to recall military equipment should result in less vio-
lent behavior and subsequently, fewer killings by LEAs.
Taken together with work that shows militarization actu-
ally leads to more violence against police (Carriere, 2016;
Wickes, 2015), the present study suggests demilitarization
may secure overall community safety. The EO represents
one avenue of demilitarization. However, given Kraska’s
(2007) typology, other aspects of militarization may be
targeted. For example, perhaps training can affect cultural
or operational militarization leading to less violent out-
comes. Future work should explore the relationship,
though the highly-decentralized nature of US police insti-
tutions presents serious challenges to systematic cross-
sectional study.
The scope of the present study allows us to derive expec-
tations at the organizational level. However, a focus on
micro-foundations may yield interesting insights. Our
paper cannot shed light on the effect of the military equip-
ment on an individual’s thought process in the field. Though
the quote above suggests some officers “just like to play
war,” others work to remind us “We’re just not out there
running around like Rambo” (Perez, quoted in Mendelson,
2016). Whereas our analyses shed light on average effects,
studies focusing on the individual level may offer more
nuanced understanding of how and when military equip-
ment affects certain officers.
Declaration of conflicting interest
The authors declare that there is no conflict of interest.
Funding
Support also provided by the Department of Political Science,
Florida State University and the School of Politics and Global
Studies, Arizona State University.
Supplementary material
The supplementary files are available at http://journals.sagepub.
com/doi/suppl/10.1177/2053168017712885.
Notes
1. Prohibited equipment includes tracked armored vehicles,
bayonets, grenade launchers, large caliber weapons and
ammunition (> 0.50 caliber). Controlled equipment (includ-
ing wheeled armored or tactical vehicles, specialized firearms
and ammunition, explosives and pyrotechnics, and riot equip-
ment) may be acquired if the law enforcement agency pro-
vides additional information, certifications, and assurances.
2. Just weeks before, US Senator Patrick Toomey introduced
a similar bill to the Senate called the “Lifesaving Gear for
Police Act” (Toomey, 2016).
3. We chose these states due to data availability. We have no
reason to believe that the data availability reflects system-
atic patterns that would affect our results. In fact, three of
the states are from the same region (New England) and have
very low crime rates. In this way, our sample represents a
hard case. Although Nevada has high crime rates, the addi-
tion of a Nevada dummy does not substantively change the
results (see Online Appendix, Table A3).
4. We chose Nevada due to the ease of seeing each county. We
have no reason to believe that Nevada is a special case. In
fact, adding a Nevada dummy does not substantively change
the results (see Online Appendix, Table A3).
5. Citations after each control list a source for theoretical justi-
fication of the variable and a source of the data.
6. We log each of the listed controls except drug use to reduce
skewness (Bland and Altman, 1997).
7. It is possible that that temporal dependencies also exist,
which could potentially affect our standard errors. To account
for this, we re-estimate all models including a dummy vari-
able for each year (using 2007 as a reference category). The
results are presented in Table A4 in the Online Appendix.
As shown, the effect of military transfers holds across all
regressions.
8. This database tracks all animals killed by police. In the
county-years included in our analysis, only dog killings
were observed.
9. Data limitations also preclude us from distinguishing
between legitimate and illegitimate forms of violence.
Carnegie Corporation of New York Grant
This publication was made possible (in part) by a grant from
Carnegie Corporation of New York. The statements made and
views expressed are solely the responsibility of the author.
References
Anderson CA, Benjamin AJ and Bartholow BD (1998) Does the gun
pull the trigger? Automatic priming effects of weapon pictures
and weapon names. Psychological Science 9(4): 308–314.
Balko R (2014) Rise of the Warrior Cop: The Militarization of
America’s Police Forces. New York, NY: Public Affairs.
Beck N and Katz J (1995) What to do (and not to do) with time-
series cross-section data. American Political Science Review
89(3): 634–647.
Delehanty et al. 7
Berkowitz L and LePage A (1967) Weapons as aggression-elic-
iting stimuli. Journal of Personality and Social Psychology
7(2): 202–207.
Bland JM and Altman DG (1997) Transformations, means, and
confidence intervals. British Medical Journal 312(7038):
1079.
Burghart BD (2015) Fatal Encounters. Available at: http://www.
fatalencounters.org/ (accessed 12 March 2016).
Carriere KR (2016) The militarization of police’s eyes, ears, and
hands: The 1033 Department of Defense program and police
safety outcomes. Master’s Thesis. Georgetown University,
Washington, DC.
Chokshi N (2014) Militarized police in Ferguson unsettles some;
Pentagon gives cities equipment.” The Washington Post.
14 August 2014. Available at: https://www.washington-
post.com/politics/militarized-police-in-ferguson-unsettles-
some-pentagon-gives-cities-equipment/2014/08/14/465
1f670-2401-11e4-86ca-6f03cbd15c1a_story.html?utm_
term=.3f263a65537a (accessed 10 March 2016).
Esri (2016) ArcGIS Desktop: Release 10.4. Redlands, CA:
Environmental Systems Research Institute.
Federal Bureau of Investigation (2010) Uniform Crime
Reporting Statistics. Available at: http://www.ucrdatatool.
gov/ (accessed 10 February 2016).
Jacobs D (1998) The determinants of deadly force: A structural
analysis of police violence. American Journal of Sociology
103(4): 837–862.
Jennings C (2016) Ratcliffe Introduces Bill to Reverse Obama’s
Executive Order on Surplus Military Equipment. Herald
Democrat. 26 March 2016. Available at: http://www.herald-
democrat.com/news/local/ratcliffe-introduces-bill-reverse-
obama-s-executive-order-surplus-military-equipment
(accessed 15 October 2016).
King G, Tomz M and Wittenberg J (2000) Making the most of
statistical analyses: Improving interpretation and presenta-
tion. American Journal of Political Science 44(2): 347–361.
Kraska PB (ed.) (2001) Militarizing the American Criminal
Justice System: The Changing Roles of the Armed Forces
and the Police. Boston, MA: Northeastern University Press.
Kraska PB (2007) Militarization and policing – its relevance to
21st century police. Policing 1(4): 501–513.
Maslow AH (1966) The Psychology of Science: A Reconnaissance.
New York, NY: Harper and Row.
Mendelson A (2016) LAUSD returns controversial rifles – but
keeps pistols and shotguns. Southern California Public Radio.
Available at: http://www.scpr.org/news/2016/02/29/57988/
lausd-s-police-force-return-military-rifles-but-st/ (accessed
16 September 2016).
Mitchell MJ and Wood CH (1998) Ironies of citizenship: Skin
color, police brutality, and the challenge to democracy in
Brazil. Social Forces 77(3): 1001–1020.
Murtha A (2016) Ratcliffe Hears Testimony from Law
Enforcement Regarding 1033 Program. Homeland
Preparedness News. 26 September 2016. Available at:
https://homelandprepnews.com/government/19811-
ratcliffe-hears-testimony-law-enforcement-regarding-
1033-program/ (accessed 3 October 2016).
Puppycide Database Project (2016) Puppycidedb.com. Available
at: https://puppycidedb.com/ (accessed 16 September 2016).
Rezvani, Pupovac J, Eads D, et al. (2014) MRAPs and bayonets:
What we know about the Pentagon’s 1033 Program. National
Public Radio. 2 September 2014. Available at: http://www.
npr.org/2014/09/02/342494225/mraps-and-bayonets-what-
we-know-about-the-pentagons-1033-program (accessed 3
March 2016).
Radil SM., Dezzani RJ and McAden LD (2017) Geographies of
U.S. police militarization and the role of the 1033 program.
The Professional Geographer 62(2): 203–213.
Ross CT (2015) A multi-level Bayesian analysis of racial bias
in police shootings at the county-level in the United States,
2011–2014. PLoS ONE 10(11): e0141854. doi:10.1371/jour-
nal.pone.0141854.
Substance Abuse and Mental Health Services Administration
(2016) National survey on drug use and health. Available at:
http://www.samhsa.gov/data/ (accessed 12 September 2016).
Sanow E (2011) Does SWAT need to be explained?” Tactical
Edge. 28 September 2011. Available at: http://freerepublic.
com/focus/f-chat/2777757/posts (accessed 3 March 2016).
The Wire (2004) Season 3, Episode 10: Reformation. HBO.
Toomey P (2016) Sen. Toomey works to restore lifesaving gear
to police, local communities. 17 March 2016. Available at:
http://www.toomey.senate.gov/?p=news&id=1704 (accessed
31 March 2016).
US Census Bureau (2016) American Community Survey 1-year
estimates, Table S0201; generated by Casey Delehanty; using
American FactFinder. Available at: http://factfinder2.census.
gov (accessed 26 September 2016).
Wickes G (2015) Demystifying “militarization”: A partial
analysis of the impact of the U.S. Department of Defense’s
“1033” equipment transfer program on police officer
safety outcomes. Master’s Thesis. Georgetown University,
Washington, DC.
