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Papers in Applied Geography
ISSN: 2375-4931 (Print) 2375-494X (Online) Journal homepage: http://www.tandfonline.com/loi/rpag20
Evaluating the Effectiveness of “No Refusal” Blood
Draw Search Warrant Programs to Reduce Alcohol-
Related Traffic Crashes in Central Texas
Christine Love Ames, Yongmei Lu & Russell Weaver
To cite this article: Christine Love Ames, Yongmei Lu & Russell Weaver (2016) Evaluating
the Effectiveness of “No Refusal” Blood Draw Search Warrant Programs to Reduce Alcohol-
Related Traffic Crashes in Central Texas, Papers in Applied Geography, 2:1, 113-120, DOI:
10.1080/23754931.2015.1114513
To link to this article: http://dx.doi.org/10.1080/23754931.2015.1114513
Published online: 21 Mar 2016.
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Application Article
Evaluating the Effectiveness of “No Refusal” Blood Draw Search
Warrant Programs to Reduce Alcohol-Related Traffic Crashes in
Central Texas
Christine Love Ames, Yongmei Lu, and Russell Weaver
Texas State University
Alcohol-related traffic crashes cause thousands of deaths a year in the United States. Many types of enforcement approaches have
been used by law enforcement agencies to decrease the amount of injuries and deaths caused by intoxicated drivers. The purpose
of this study is to evaluate the effectiveness of the “no refusal”blood draw programs used by law enforcement agencies in the
Capital Area Council of Governments and the Alamo Area Council of Governments of central Texas. The study area covers
twenty-three counties that are served by more than 120 municipal, county, and other law enforcement agencies. A difference-in-
differences method was applied to analyze the alcohol-related crash rates before and after the no refusal program. Statistically
significant reductions in the alcohol-related crash rate after the adoption of no refusal programs were revealed, suggesting the
effectiveness of the program in reducing alcohol-related traffic crashes. Keywords: alcohol-related traffic crash, difference-
in-differences analysis, no refusal program.
Driving under the influence of alcohol (DUI) is a
national health and safety problem in the United
States. It is frequently associated with property dam-
age, bodily injury, and death (Razvodovsky 2003; Fel-
son, Burchfield, and Teasdale 2007). A well-known
case in central Texas was the fatality of twenty-seven-
year-old San Antonio Police Officer Stephanie Brown,
killed by a drunk driver who was driving the wrong
way on Interstate 35. According to the National High-
way Traffic Safety Administration (NHTSA) in 2012,
1,170 people throughout Texas were killed and
another 9,458 people were seriously injured in alco-
hol-related crashes. On average, an alcohol-related
crash occurs in Texas every twenty minutes. Nation-
wide, there is an alcohol-related traffic death every
fifty-one minutes (NHTSA 2012).
Several laws have been passed by federal and state
legislators to combat this problem including a mini-
mum legal drinking age (MLDA), a blood alcohol
concentration (BAC) limit of 0.08 g/dL when operat-
ing a vehicle, and no-tolerance sanctions for underage
drinkers. Different approaches have been used by law
enforcement agencies to carry out these laws. Exam-
ples include public education presentations, high-visi-
bility enforcement (HVE), sobriety checkpoints,
specialized driving while intoxicated (DWI) enforce-
ment units, and “no refusal”blood draw weekends
(Shults et al. 2001; Fell, Ferguson, et al. 2003; Fell,
Tippetts, and Levy 2008).
In Texas, the initiative of no refusal weekends has
become a popular enforcement strategy, partially because
the enforcement efforts such as sobriety checkpoints and
warrantless blood draws have been deemed unconstitu-
tional by the Texas Court of Criminal Appeals. Sobriety
checkpoints were ruled unconstitutional in Texas in 1994
before a study could have been conducted to evaluate the
effectiveness of such sobriety checkpoints. Texas law
enforcement agencies used to rely on specificmandatory
blood draw authorizations to take blood from drivers who
investigating officers believed were intoxicated due to the
officers’observations of driving behaviors, driver behaviors,
and signs of intoxication. In 2014, the Texas Court of
Criminal Appeals ruled these enforcement methods
unconstitutional.
Agencies now rely on search warrants to draw blood
from drivers who officers believe are intoxicated. Many
departments in Texas have initiated no refusal weekends
during holidays or long weekends when more people tend
to be intoxicated. During the actual program periods, law
enforcement will conduct themselves as they would any
other weekend, but if they have probable cause to believe a
driver is intoxicated, and if the driver refuses to provide a
blood sample, the officer will have the ability to obtain a
search warrant for that specimen. Judges remain on call the
entire weekend to sign these warrants, which is where the
“no refusal”moniker originated. These programs typically
begin with publicized announcements through the media,
warning drivers that if they are stopped by law enforcement
on these particular weekends, a search warrant will be
issued for their blood if the officer has probable cause to
believe that an individual is intoxicated.
These no refusal weekend programs have only been
implemented during the last decade, and therefore
have not been examined systematically for their effec-
tiveness yet. The purpose of this study is to evaluate
the effectiveness of the no refusal weekend programs
in the areas served by the law enforcement agencies in
the Capital Area Council of Governments (CAPCOG)
Papers in Applied Geography, 2(1) 2016, pages 113–120 © 2016 Applied Geography Conferences.
Published by Taylor & Francis Group, LLC.
Downloaded by [Texas State University, San Marcos] at 07:24 22 March 2016
and the Alamo Area Council of Governments
(AACOG) in central Texas. These two associations
cover twenty-three counties that are served by more
than 120 municipal, county, and other law enforce-
ment agencies (Figure 1).
The research question for this study is to investigate
if the implementation of no refusal programs helps to
reduce the alcohol-related crash rates within an
agency’s jurisdiction. The null hypothesis is that there
is no significant difference in the rate of alcohol-
related crashes when a no refusal program was in place
with normal patrol enforcement.
Background
Texas Penal Code defines DWI as an offense that
occurs when a person is intoxicated while operating a
motor vehicle in a public place. The definition of
intoxication in the Texas Penal Code is “not having
the normal use of mental or physical faculties by
Figure 1 The study areas of the Capital area council of governments (CAPCOG) and the Alamo area council of govern-
ments (AACOG). (color figure available online.)
114 Ames et al.
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reason of the introduction of alcohol, a controlled sub-
stance, a drug, a dangerous drug, a combination of two
or more of those substances, or any other substance
into the body; or having an alcohol concentration of
0.08 g/dL or more”(Lexis Nexis Group 2014a, 175).
The NHTSA has kept records of alcohol-related
traffic fatalities in the United States since 1982. When
the NHTSA analyzed its records that first year, it was
determined that 35 percent of all fatal crashes involved
a driver with a BAC above the legal limit. In 2012, this
number reduced to 21 percent. Although this progress
has been cited as remarkable and substantial, alcohol-
related traffic crashes still accounted for 10,322 fatali-
ties in 2012 (Shults et al. 2001; NHTSA 2012; Fell
et al. 2015).
During this same period, federal, state, and local
agencies began implementing strategies to counter
this widespread problem. In 1984, federal legislation
was passed requiring states to raise their minimum
legal drinking age from eighteen to twenty-one years
old or accept the consequence of withheld federal
highway funds. By 1987, the legal drinking age in all
fifty states was twenty-one years of age. Congress
acted again in 2001, requiring that states lower their
legal BAC from 0.10 g/dL to 0.08 g/dL or federal
funding would again be withheld (Shults et al., 2001;
23 U.S.C. x163).
Logically, legal sanctions have little weight without
actual enforcement, which is typically left to local law
enforcement. It is in local communities that these laws
are enforced and reductions in alcohol-related traffic
crashes save lives. Agencies have been using many
strategies to enforce these laws, such as sobriety check-
points, HVE, specialized DWI units, and most
recently no refusal blood draw search warrant opera-
tions (Dula, Dwyer, and LeVerne 2007; Fell, Tippetts,
and Levy 2008; Fell et al. 2014; Wiliszowski and Jones
2003; Williams 2006).
Enforcement of these particular laws comes at a
cost, and must compete against other police responsi-
bilities. Administrators, legislators, and the patrol offi-
cers tasked with these endeavors can benefit from
research that provides answers to which efforts are
more effective and efficient. A number of studies have
been conducted over the past three decades to deter-
mine the effectiveness of these laws, as well as the
allotted enforcement efforts. These studies have
shown certain relationships between the two, although
some authors were disappointed by the lack of findings
in their analyses. It has been noted by many studies
that specific types of enforcement might work differ-
ently for agencies of distinct sizes, capabilities, and
manpower (Foss, Stewart, and Reinfurt 2001; Elder
et al. 2002; Wagenaar and Toomey 2002; Bernat,
Dunsmuir, and Wagenaar 2004; Dula, Dwyer, and
LeVerne 2007; Fell, Tippetts, and Levy 2008; Newby
and Nunn 2011; Fell et al. 2015).
Raising the MLDA to twenty-one has been the most
well-studied alcohol-related policy in the United
States. Wagenaar and Toomey (2002) reviewed
seventy-nine studies that included a longitudinal
design, comparison groups, and probability sampling
or use of a census to analyze the effects of the MLDA
and traffic crashes. They reported that more than half
of the studies found a higher MLDA was related to a
decrease in traffic crashes.
Lowering the legal BAC limit from 0.10 g/dL to
0.08 g/dL has also been extensively researched.
Although the specific effects of the decrease in the
BAC limit vary from state to state, many articles
revealed a significant relationship between the imple-
mentation of 0.08 g/dL BAC laws and a decrease in
alcohol-related traffic crashes. Bernat, Dunsmuir, and
Wagenaar (2004) concluded that, “reductions in the
legal limit in the United States over the past decade
are saving hundreds of lives per year, and further mor-
tality reductions are likely”(498). Nonetheless, other
studies found no relationships (Johnson and Fell 1995;
Foss, Stewart, and Reinfurt 2001; Cowan and Joffie
2002; Tippetts et al. 2005; Fell and Voas 2006; Free-
man 2007).
Dee (2001) conducted a difference-in-differences
(DID) analysis on the effects of BAC laws and
concluded that the states that adopted a 0.08 g/
dL BAC law reduced their total traffic fatalities
by 7.2 percent. A similar DID analysis by Eisen-
berg (2003) also found the 0.08 g/dL BAC law
was effective in reducing traffic fatalities. Free-
man (2007) tested for serial correlation in addi-
tion to the DID method, and found that BAC
standards in combination with automatic license
revocation were effective in reducing traffic-
related deaths.
Voas, Holder, and Gruenewald (1997) found pos-
itive results when media were combined with DWI
enforcement. The authors totaled the number of
times an enforcement effort was mentioned on the
news and then analyzed telephone surveys to deter-
mine the public’s perception of apprehension risk.
The results of other studies regarding media varied
widely. Some studies show little to no relationship
between media usage and enforcement efforts (Tay
2005; Erke, Goldenbeld, and Vaa 2009), whereas
others find a statistically significant relationship
among media attention, enforcement efforts, and
the subsequent decline in alcohol-related crashes
(McCaul and McLean 1990; Elder et al. 2004;
Miller, Blewden, and Zhang 2004; Fell, Tippetts,
and Levy 2008).
A study by Fell et al. (2014) found that higher
numbers of sworn officers,aswellashighernum-
bers of DUI arrests, were both significant in
reducing alcohol-related crashes. The authors
noted this relationship was plausible, as more
drivers would see roadside traffic enforcement,
increasing the potential consequences of DUI.
Although these studies used different variables to
describe HVE, most studies found a relationship
between their variables and alcohol-related
crashes (Voas, Holder, and Gruenewald 1997;
“No Refusal”Blood Draw Search Warrant Programs 115
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Shults et al. 2001; Stewart and Fell 2002; Dula,
Dwyer, and LeVerne 2007; Fell et al. 2014).
For many years, some states have been using partic-
ular enforcement parameters that give police officers
the right to draw an individual’s blood without his or
her consent. Specifically, Texas has several mandatory
blood draw requirements, which are statutory author-
izations detailed in Texas Transportation Code
724.012. In specific circumstances—for example, a
crash in which an individual is severely injured and an
involved driver is suspected of DUI—officers on scene
can order the suspected individual’s blood drawn with-
out his or her consent to determine a BAC level (Lexis
Nexis Group 2014b). However, recent rulings by both
the U.S. Supreme Court and the Texas Court of
Criminal Appeals have determined these mandatory
blood draws violate individuals’Fourth Amendment
rights, and the related blood draws have been ruled
unconstitutional (Missouri v. McNeely 2013; Texas v.
Villarreal 2014). To our knowledge, there is a lack of
research on the effectiveness of these mandatory blood
draw programs in reducing alcohol-related traffic
crashes.
Law enforcement officers in Texas are now required
to obtain a search warrant to draw blood from an indi-
vidual they suspect of DWI or DUI. Since Halloween
of 2008, the Austin Police Department has imple-
mented “no refusal weekends”on holidays when
impaired drivers are more prevalent. Judges are avail-
able throughout the weekend to sign probable cause
search warrants for blood draws.
Although other areas of enforcement have been
researched, the application of no refusal search
warrants is a relatively new enforcement strategy
on which little research has been conducted. Many
people do not believe in a blanket solution for all
law enforcement agencies as a whole to combat
alcohol-related traffic crashes, but DWI and DUI
is a habitual problem. The effectiveness of new
enforcement strategies needs to be explored as the
data become available. The empirical analyses
reported in the rest of this article aim to provide
an early examination of the effects of no refusal
programs in reducing alcohol-related trafficcrashes
after they are implemented by some law enforce-
ment agencies in central Texas. Alcohol-related
traffic crashes will be compared for the time peri-
ods before and after the no refusal programs.
Data and Methods
This study performed a DID analysis to assess whether
selected Texas municipalities that implemented no
refusal programs in 2011 experienced reduced alco-
hol-related crash rates relative to a control group of
municipalities that did not participate in no refusal
programs. Each county in Texas is part of a council of
governments (COG), where a COG is an association
with the Texas Association of Regional Councils
(2014) that deals with the needs that overlap individual
local governments or require regional attention. The
services of these associations vary depending on the
needs of the regions, but they include resources such
as operating law enforcement training academies,
maintaining and improving regional 9-1-1 systems,
and promoting regional economic development. This
study examines two COGs: the CAPCOG and the
AACOG. These two areas cover approximately 19,834
square miles with a population of more than 4 million
individuals.
CAPCOG and AACOG serve twenty-three coun-
ties: Bastrop, Blanco, Burnet, Caldwell, Fayette, Hays,
Lee, Llano, Travis, Williamson, Atascosa, Bandera,
Bexar, Comal, Frio, Gillespie, Guadalupe, Karnes,
Kendall, Kerr, McMullen, Medina, and Wilson, as
shown in Figure 1. These counties include more than
123 municipalities, along with a multitude of munici-
pal law enforcement agencies, sheriff’s departments,
and university agencies. The service areas of municipal
law enforcement agencies were the unit for this analy-
sis. The time period of interest for this study, 2011,
was selected because it marked a year in which fifteen
agencies adopted some form of a no refusal program.
Next, the Texas Department of Transportation
(TxDoT) publishes Texas motor vehicle crash statis-
tics each year. These statistics are collected through
the Texas Peace Officer’s Crash Reports (CR-3),
which are maintained through a statewide automated
database. This database is currently published for the
years 2003 through 2013 (TxDoT 2015). These
reports are completed in accordance with the Texas
Transportation Code 550.062 Officer’s Accident
Report. The data used for this study include the
reported traffic accidents during the years 2006 to
2013; the TxDoT tables prior to 2006 did not include
municipal information.
The crash reports include information such as the
location of the crash, drivers and passengers involved
in each vehicle in a crash, as well as specific circum-
stances that might have contributed to the cause of the
crash. These circumstances contain sections on
whether any drivers had been drinking, were under
the influence of alcohol, and whether any citations
were issued or arrests made.
The specific information gathered from the TxDoT
statistics tables included all of the crashes reported for
each city in the CAPCOG and AACOG jurisdictions,
as well as all of the crashes that involved drivers under
some influence of alcohol. The term DUI is inter-
changeable with the term DWI for this study using
the TxDoT definition of a DUI crash. A DUI crash is
defined by TxDoT as any vehicle crash that might
have had a contributing factor of alcohol.
The contributing factors of vehicle crashes are
reported via the CR-3 Texas Peace Officer’s Crash
Reports. These crash reports have two separate sec-
tions for alcohol involvement under “Factors and
Conditions.”Officers add what they believe to be alco-
hol-related contributing factors to the cause of a crash,
116 Ames et al.
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which can be defined as “had been drinking”or “under
the influence of alcohol.”The term had been drinking
refers to any observations the officer makes that would
indicate a driver has been drinking. The officer might
not be of the opinion that the driver is over the legal
limit of a 0.08 g/dL BAC level, but might believe that
the fact the driver had been drinking was a contribut-
ing factor in the vehicle crash.
The term under the influence of alcohol refers to a
driver who the officer believes is at or above the legal
intoxication level of 0.08 g/dL. This could be based on
the officer’s observations, as well as standardized field
sobriety tests, or a blood or breath sample. If a blood
or breath sample was taken from the driver, the results
of the sample are added to the driver portion of the
crash report.
As noted previously, not all of the 123 cities in the
CAPCOG and AACOG jurisdictions maintain munic-
ipal law enforcement agencies, which reduced the uni-
verse of usable observations to ninety-six agencies.
Furthermore, as crash data were unavailable for some
agencies, or some agencies did not report a sufficient
number of crashes in a given year, this universe was
reduced by twenty-five additional agencies, thereby
leaving a total of seventy-one agencies.
Each of the seventy-one remaining municipal law
enforcement agencies was contacted to determine if
the agency participates in a no refusal program, and if
so, when the program began. Out of the seventy-one
agencies that were contacted, forty-five responded (for
a 63.4 percent initial response rate). The year in which
a no refusal program began for each agency was
recorded. As an example, the San Antonio Police
Department began its no refusal weekend program on
Memorial Day weekend in 2008, and then increased
to a year-round program in 2011.
The year that the most agencies in the sample data
set began no refusal programs was 2011, which was
then determined to be used as the focal time period
for the DID analysis. To determine whether the
municipal law enforcement agencies that participate
in no refusal programs have a decrease in alcohol-
related crashes after the program implementation
compared to the agencies that do not participate, data
were obtained for the two years prior as well as the
two years after 2011. The agencies that began a no
refusal program before 2011 were excluded from fur-
ther analyses, as well as the agencies that began no
refusal programs after 2011. This exclusion was made
so that the DID analysis would not be influenced by
early or late adopters. These exclusions left the
researchers with a total analytical sample of forty
agencies. Fifteen of these agencies began participating
in no refusal programs during 2011, and the other
twenty-five did not have programs in place. The
DUI crash rate was determined by dividing the num-
ber of DUI crashes for a given year by the total num-
ber of crashes for the same year for each
municipality. For this sample, the average annual
DUI crash rate “before”the no refusal policy change
was computed with the data for 2009 and 2010, and
the average annual DUI crash rate “after”the policy
change was computed with the data for 2012 and
2013. These measures are used as the pre and post
average annual DUI rates for the analysis.
That being said, in general DID analysis can be used
to estimate the effect of a policy change by comparing
the pre- and postchange differences in the mean of a
given outcome variable between a treatment group
(i.e., the group that adopted the policy change) and a
control group that did not experience the same policy
change (Abadie 2005). More precisely, a DID estima-
tor subtracts the mean difference measured in that
quantity between two groups before some treatment is
applied, from the mean between-group difference
after the treatment occurs. Any observed pretreatment
difference is presumably the result of variation in
unobserved group-level attributes. Assuming that
these unobserved attributes do not vary with time, the
“before”difference between groups should equal the
“after”difference, plus any effect from the treatment
(Gerber and Green 2012). Let txrepresent this aver-
age treatment effect on some variable x. The DID esti-
mate is then computed as:
txDxT;tD1
¡xC;tD1
¡xT;tD0
¡xC;tD0
where xis the mean of variable x, T (C) indicates
the treatment (control) group, tD0 denotes the
pretreatment time period, and tD1 denotes the
posttreatment time period.
For this study, jurisdictions that established a no
refusal program in 2011 make up the treatment group,
and those that did not participate in no refusal pro-
grams are the control group. To calculate the DID
estimate, or the treatment effect, dummy variables
were created to represent the pre and post time peri-
ods. A dummy variable was also created for the agen-
cies that began the no refusal program in 2011. An
interaction variable was then created between the post
and no refusal variable. With these variable specifica-
tions, the coefficient estimated on the interaction
between the post and no refusal variables in a linear
regression, wherein the response variable is the DUI
crash rate, will be equal to the treatment effect of the
no refusal program. The regression equation takes the
following form:
yDb0Cb1Post Cb2NoRefusal Cb3Post
NoRefusal Ce
where b0is the intercept, Post is the dummy vari-
able indicating that the response variable was
measured in the time period after 2011,
NoRefusal is the dummy variable that indicates
whether an agency began participating in a no
“No Refusal”Blood Draw Search Warrant Programs 117
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refusal program in 2011, b3is the DID estimate
on the interaction variable, and eis a normally
distributed error term.
Essentially, the DID method first computes the pre
crash rates for the participating and nonparticipating
agencies for the years 2009 and 2010. The difference
between the participating and nonparticipating agen-
cies is derived. The same computation is completed
for the two groups for 2012 and 2013, after the imple-
mentation of the programs in 2011. If the no refusal
programs have no effect on the crash rate of the partic-
ipating group, the crash rates should continue the gen-
eral trend over the time period (and b3should equal
zero). If the no refusal program has an effect on the
participating group, then b3will be nonzero.
Results and Discussion
During 2009 and 2010 the crash rates of both the par-
ticipating and nonparticipating agencies did not show
any general trends or significant difference in crash
rates before the implementation of the no refusal pro-
grams in 2011. The DID analysis of the crash rates
during the post no refusal programs in 2012 and 2013
revealed a moderately significant reduction in crash
rates from nonparticipating agencies (p<0.10), as
shown in Table 1.
This study was quasi-experimental; the agencies
included in this study were not selected randomly, but
participated in no refusal programs voluntarily based
on each agency’s subjective needs and available resour-
ces. Although confounding factors might muddle the
ability of the DID analysis to show the precise signifi-
cance of the no refusal programs, the analyses revealed
that the use of no refusal programs has reduced the
alcohol-related crash rate within CAPCOG and
AACOG’s jurisdictions. Alcohol-related crashes are a
national health and safety problem. Any step in reduc-
ing these crashes could be an important achievement
considering the number of lives that might be saved.
Policymakers and law enforcement administrators
must prioritize their enforcement efforts based on the
available manpower, monetary resources, and commu-
nity needs. Empirical results such as these might assist
those individuals in deciding whether or not programs
such as no refusal warrants would benefit their com-
munities. If more agencies adopt a no refusal program,
more data will be available to be collected and further
research can be conducted to establish a better stan-
dard of how effective these programs are.
It is important to notice possible diffusion effects
from the success of no refusal programs in a certain
jurisdiction. Many agencies in the study area have cho-
sen to begin no refusal programs during the study
period. As shown in Figure 1, many other agencies
have implemented no refusal programs, but they were
not included in this examination because sufficient
data were not available to perform a DID analysis for
these municipalities.
There are some limitations of the data used for this
study. Official statistics concerning criminal events
always have an error margin because not all crimes are
reported to law enforcement agencies. When dealing
with crashes and alcohol, there will be gaps where
individuals have left the scene of a crash or have been
undetected by law enforcement. It is also an issue that
vehicle accidents that only caused vehicle damages
might not be reported in a crash report and therefore
these crashes were not included in the analyses
reported by this article. If a driver is arrested in one of
these incidents, an arrest report may be generated
instead of a crash report. It is unknown to the authors
at this time how much these incidents could affect the
analysis.
The no refusal initiative is a relatively new enforce-
ment approach that, to the authors’knowledge, has
not been analyzed for its effectiveness for reducing
alcohol-related crashes. This study used the best data
available for the current time frame; it is also a goal of
the author to start building longitudinal data over time
for future research. Future studies could include more
population-level socioeconomic and demographic data
as well as data on drinking establishments and sales.
Incorporating more comprehensive and detailed data
will enable future studies to conduct more accurate
assessment on the effectiveness of no refusal programs
to guide the adoption of such programs by law
enforcement agencies.
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*
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Note: DUI Ddriving under the influence.
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“No Refusal”Blood Draw Search Warrant Programs 119
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CHRISTINE LOVE AMES is a Graduate Assistant in the
Department of Geography, Texas State University, San Mar-
cos, TX 78666. E-mail: CL25@txstate.edu. Her research
interests include GIS and spatial analysis of crime.
YONGMEI LU is a Professor in the Department of Geogra-
phy, Texas State University, San Marcos, TX 78666. E-mail:
YL10@txstate.edu. Her research interests include GIScience
and the application of GIS in Crime, Health, and Urban and
Environmental studies.
RUSSELL WEAVER is an Assistant Professor in the
Department of Geography, Texas State University, San Mar-
cos, TX 78666. E-mail: rcweaver@txstate.edu. His research
interests include community and regional economic develop-
ment, planning, and policy.
120 Ames et al.
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