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Criminal Justice Policy Review
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DOI: 10.1177/08874034211026366
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Article
AMBER Alert Effectiveness
Reexamined
Timothy Griffin1, Joshua H. Williams2,
and Colleen Kadleck3
Abstract
Prior research based on limited datasets has suggested AMBER Alerts do little to
prevent harm to child abduction victims. However, to investigate the possibility of
recent improvements in AMBER Alert performance, the authors examine a sample
of 472 AMBER Alerts issued over a 3-year period from 2012 to 2015, using available
media accounts to code for relevant case information. The findings are consistent
with prior research questioning AMBER Alert effectiveness: The crucial variable
predicting Alert outcomes is abductor relationship to the victim, not AMBER
Alert “performance.” Furthermore, cases involving “successful” AMBER Alerts
are comparable on measurable factors to AMBER Alert cases where the child was
recovered safely but the Alert played no role, suggesting both categories of cases
involved little real risk. Implications for interpreting the viability of the AMBER
Alert concept, public discourse regarding its contribution to child safety, and larger
implications for crime control policy are discussed.
Keywords
AMBER Alert, child abduction, criminal justice policy
Introduction
The AMBER Alert child recovery system was inspired by the abduction and murder of
Amber Hagerman in Arlington, Texas, in 1996 (Griffin et al., 2007). Public dismay at
the brutality of the murder and inability of law enforcement to appeal for public
1University of Nevada, Reno, USA
2VK Strategies, London, UK
3University of Nebraska Omaha, USA
Corresponding Author:
Timothy Griffin, University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV 89557, USA.
Email: tgriffin@unr.edu
1026366CJPXXX10.1177/08874034211026366Criminal Justice Policy ReviewGrin et al.
research-article2021
2 Criminal Justice Policy Review 00(0)
assistance in the search for the missing child inspired the creation of the first “Amber
Plan” in Texas in 1996. The system was eventually expanded, federalized, and unified
across the United States under the PROTECT Act of 2003, and at the time this article’s
completion, the U.S. Department of Justice reports, “1064 children [have been] res-
cued specifically because of AMBER Alert [and] 92 children have been rescued
because of Wireless Emergency Alerts.” (U.S. Department of Justice, Office of Justice
Programs, 2021a, emphasis added). AMBER Alerts are issued when authorized law
enforcement personnel, upon learning of a missing child case, assess the circumstances
to determine if there is enough evidence of threat and useable information to issue an
AMBER Alert to solicit the public’s assistance in searching for the child. AMBER
Alerts can then be publicized through television, news websites, electronic road signs,
radio announcements, and social media in an effort to elicit the public to quickly assist
law enforcement (U.S. Department of Justice, Office of Justice Programs, 2021b).
Although AMBER Alert system operators, advocates, and members of the public
have expressed enthusiasm for the system’s achievements, prior research has sug-
gested these claims are exaggerated. The children recovered because of AMBER Alert
are rarely “rescued” rapidly, which is a crucial consideration in light of research
showing that most child abduction-murders end within hours of their initiation (see
Brown et al., 2006). Furthermore, there are little evidence abductors in AMBER Alert
“success” cases posed serious threats to the children recovered (see Griffin, 2010;
Griffin et al., 2007, 2016). The crucial variable determining “safe recovery” in
AMBER Alerts (what happens to the abducted children, which is not the same as
whether the Alerts had any “effect”—a crucial distinction which will be revisited)
appears to be the identity and apparent nature of the abductors and their likely inten-
tions. AMBER Alert “failures,” however, were simply tragedies for which there was
likely no possible intervention. Prior research has also suggested the AMBER Alert
concept is inherently problematic, as it requires too many improbable things to work
perfectly in short time frames when information is scant and suspect (Griffin & Miller,
2008). Nonetheless, prior research questioning the system’s ability to prevent harm
has generally relied on incomplete sampling frames and earlier data (see Griffin, 2010;
Griffin et al., 2007, 2016), which theoretically could miss AMBER Alert effective-
ness. It is also at least plausible issuing authorities’ increased familiarity with the
system, along with broader public awareness, possibly brought about in part by its
expansion into social media, has improved AMBER Alert outcomes.1
In this paper, using the case attributes provided by media accounts of 472 AMBER
alerts issued in the United States and Canada from 2012 to 2015, we evaluate these
possibilities by providing logistic regression models to tap the apparent predictors of
“safe recovery” (children recovered alive and/or unharmed) in AMBER Alert cases.
We also statistically compare “success” cases (where the Alert had some effect leading
to safe recovery) to “safe-recovery-no-effect” cases (where the child[ren] were recov-
ered unharmed but the Alert had no effect) along known with measurable variables to
gain insight into the level of “threat” actually posed in cases where AMBER Alert
“succeeded.” These analyses can shed light on whether any potential significant
Griffin et al. 3
improvement in the performance of AMBER Alerts has been achieved in the years
since its inception.
Literature Review
The available literature on the effectiveness of AMBER Alert strongly suggests the
system is sharply limited in its ability to save endangered children’s lives or prevent
serious harm in clearly high-risk child abduction scenarios, and it is in fact usually
deployed in cases most likely evaluated as low risk. For example, the first attempt to
analyze AMBER Alert cautioned it was in danger of becoming trivialized owing to the
apparently mundane cases for which it was routinely deployed, such as familial abduc-
tions (Hargrove, 2005). This analysis, perhaps inadvertently, was the first suggestion
of a fundamental problem vexing AMBER Alert issuance decisions: The assessment
of threat by issuing authorities in short time frames based on ambiguous and evolving
information—an issue which will be revisited in the subsequent discussion of the find-
ings provided here.
More complete and systematic collation of AMBER Alerts in the United States is
provided by the National Center for Missing and Exploited Children (NCMEC, 2007,
2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020),
which has published annual summaries of AMBER Alert cases for the years of 2006
to 2019. The Center’s data analysis focus is the aggregated descriptive attributes of all
cases for respective years (such as how often Alerts were “effective,” average delay
between the issuance of the Alert and recovery, basic overall victim and offender char-
acteristics) and is not designed for analyses involving individual case attributes.
Nonetheless, data from the Center still provide valuable insights into the system’s
possible limitations. In fact, our calculation of consolidated Center data shows that
approximately 87% of AMBER Alert cases end with the abducted children recovered
alive (NCMEC, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017,
2018, 2019, 2020). Taken at face value, this seems to suggest the system is highly
effective, and this high recovery rate has actually been cited publicly by system advo-
cates and journalists (ABC 13 Eyewitness News, 2019; The Associated Press, 2006),
and even equated with the word “success (Gonzalez, 2016).”
However, when one probes deeper into the NCMEC data it is clear the high “safe
recovery” rate conflates two ideas—safe recovery because the Alert had some effect,
and safe recovery because of something else, such as normal law enforcement investi-
gation. When an AMBER Alert is issued, law enforcement officials do not simply wait
for the Alert to work; they keep looking for the victims and offenders. In fact, the data
imply it is their efforts—not AMBER Alerts—which generally lead to safe recovery in
AMBER Alert cases. The consolidated annual reports show that, even though the vast
majority of children in AMBER Alert cases are indeed recovered safely, most Alerts
have no effect, and in fact, the average actual “success” rate (where the Alert had some
effect) is only 26.7%, based on our calculation of consolidated NCMEC data after
non-abduction cases are removed from the analysis. (National Center for Missing &
Exploited Children, 2007–2020). By this use of the word “success,” the data analysts
4 Criminal Justice Policy Review 00(0)
at the Center mean AMBER Alerts actually contributed to the recovery of the abducted
children either because of a citizen tip, because the perpetrators were intimidated by
the Alert into surrendering or releasing the children, or some other means by which the
AMBER Alert was deemed to have made a difference. Thus, even though the vast
majority of the children in AMBER Alert cases is in fact recovered safely, AMBER
Alerts usually have nothing to do with that positive result (NCMEC, 2007, 2008,
2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020) and are
what the present authors refer to as “safe-recovery-no-effect” cases. To iterate, “safe
recovery” almost always occurs in AMBER Alert cases, but usually not because the
system was “successful.” A concrete example would be where a toddler is abducted by
a noncustodial parent believed to pose a threat, an AMBER Alert is issued, and then
investigators locate and recover the child, but the Alert played no role in this safe
recovery. Most AMBER Alert cases, in fact, roughly fit this model. This again high-
lights the crucial distinction between “safe recovery” as opposed to an AMBER Alert
“success” because of some “effect.”
There have also to date been a few examples of peer-reviewed examinations of
AMBER Alert effectiveness. All of them strongly suggest a number of general conclu-
sions. First, a minority of AMBER Alerts do in fact contribute tangibly to the recovery
of some abducted children. Varying definitions of AMBER Alerts having an “effect”
have yielded “success” rates of 31% (Griffin et al., 2007) and 26% (Griffin et al.,
2016), which is consistent with the average of 26.7% we derived from the official
reports provided by NCMEC (see above), and affirms that most AMBER Alerts have
no effect whatsoever—again, even though “safe recovery” is almost always achieved.
Furthermore, a number of other fairly sobering findings have also emerged from
this limited body of literature. First, unlike the NCMEC reports, this prior research has
estimated the delays between the abduction and recovery, which the NCMEC data do
not provide, and those delays are usually much longer than 3 hr. For example, Griffin
and coauthors (2016) reported that only 46 of 448 AMBER Alert cases involving an
authentic abduction led to recovery within 3 hr of the abduction, and in most of those
cases the AMBER Alerts had no effect. Furthermore, an analysis of AMBER Alert
“success” cases showed that only 15.3% of the successes involving recovery within 3
hr (Griffin, 2010). This is important because available literature indicates the over-
whelming majority of the victims of child abduction-murder are killed within 3 hr of
their abduction, and almost half are killed within 1 hr (Brown et al., 2006; Hanfland
et al., 1997). For instance, Brown and Keppel (2007) found that among a sample of
735 child-abduction murders, the time-span between initial contact and time of the
murder is <1 hr in 53% of cases. This strongly suggests if AMBER Alerts are to be
considered “successful” at rescuing children from life-threatening circumstances the
recovery delays in AMBER Alert cases would have to routinely be much faster than
what has been reported in the available literature. If recovery times in AMBER Alert
“success” cases are not relatively swift, it begs the question of how much threat was
really posed since motivated perpetrators had sufficient time to act on their worst
intentions.
Griffin et al. 5
Another recurring finding from this earlier body of literature is that when one
examines the nature of the abductors in “successful” AMBER Alert cases (again,
where the Alert had some “effect”), there is no compelling reason to believe, at least
based on available information, that the abductors in such cases present life-threaten-
ing risk to the children abducted (Griffin, 2010). The overwhelming majority of
AMBER Alert success cases involve abductors quite unlike the stereotypical predator
(see Sedlak et al., 2002). They tend to be family members or significant others acting
in the heat of custody disputes or domestic discord, wayward babysitters, car thieves
unaware of the presence of an unattended child at the moment of the crime, and other
categories of abductor whose known attributes do not clearly indicate harmful inten-
tions (Griffin, 2010; Griffin et al., 2007). It is certainly true AMBER Alerts were
“effective” in those cases and thus could be deemed “successes,” but suggesting the
victims were “rescued” from clear danger is special pleading, especially in light of
prior literature showing that most children in AMBER Alert cases are recovered
unharmed even though most AMBER Alert cases have no effect (see above).
Further still, prior research has also shown that what could be facially regarded as
evidence of “threat” in AMBER Alert cases—violence against parties other than the
child, or “peripheral harm”—is, in fact, a negative predictor of harm to the abducted
children (Williams et al., 2017). The evidence strongly suggests this finding is driven
by the behaviors of emotionally distraught abductors in family abduction cases; such
perpetrators likely have no violent intentions toward the children they abduct even if
they are willing to use instrumental violence against others attempting to foil them.
This finding further illustrates the difficulty of estimating “threat” in AMBER Alert
cases, as well as a possibly intractable problem confronting AMBER Alert system
operators: predicting human behavior in short time frames with scant, evolving infor-
mation of uncertain quality (Griffin & Miller, 2008).
The available literature also suggests there is a daunting problem in assessing
AMBER Alert: The impossibility of knowing with certainty what “would have” hap-
pened in any particular AMBER Alert case if an AMBER Alert had not been issued.
No experimental designs have been conducted where the survival rates in AMBER
Alert-approved cases have been compared with those of a control group of approved
cases randomly assigned to a “no Alert” condition. Thus, researchers, like issuing
authorities, have to rely on plausible speculation and proxy measures of “risk” or
“threat.”
The literature also points to another problem vexing evaluators: How is “success”
defined? When system operators point to the high “safe recovery” rate, this again can
be misleading because it could allow for the classic association-versus-causation con-
fusion by errantly implying the AMBER Alerts “caused” the children to be safely
recovered. However, that cannot be the case, because again AMBER Alerts have no
effect in the overwhelming majority of cases that end in safe recovery. This means the
primary reason(s) for safe recovery in AMBER Alert cases are something other than
AMBER Alert (such as routine investigation), and evaluating the system’s utility
requires a more nuanced examination of available case details than merely whether the
6 Criminal Justice Policy Review 00(0)
child was recovered alive and/or unharmed, or the Alert had some “effect” and was,
therefore, “successful.”
Nonetheless, it must be iterated that prior empirical examinations of the “effective-
ness” of the AMBER Alert system have relied on incomplete sampling frames and
generally earlier data, and it is entirely plausible there have been improvements in the
system’s efficiency. Furthermore, the expansion of the system’s scope, including its
introduction onto social media platforms, might have improved its performance. Thus,
any analysis of AMBER Alert effectiveness would do well to improve on earlier efforts
in two ways. First, a more thorough sampling frame unlikely to miss any exemplary
AMBER Alert success cases should be deployed. Second, data from more recent years
could reveal any improvements in system operation over time.
Current Study
Data
To create a data set allowing for analysis of the attributes of individual AMBER Alert
cases, the authors enrolled in the Google News Alert system from June 2012 until June
2015, using the search term “AMBER Alert” to flag possibly relevant stories, for
which links would be sent via email from the Google news service. On a daily basis,
summaries of national and regional level news outlets with stories including the term
“AMBER Alert” were received and coded. Although not all of these stories were direct
reports about AMBER alert abduction cases, many provided crucial information about
real abductions where Alerts were issued. Among these were (sporadically available)
victim and offender demographic information, victim-offender relationship, and
approximate or specific abduction and recovery times (or directly stated intervals).
The news reports also typically contained enough information to determine if the chil-
dren were recovered, whether the Alert had any effect in bringing about that recovery,
and whether they suffered any harm or were killed.
These stories were copied and pasted onto labeled Word documents for future refer-
ence during data cleaning. Student volunteers inputted relevant coded information
from these documents onto an Excel spreadsheet for data cleaning and converging,
after which the data were transferred to a STATA file for statistical analysis. Through
this process, potentially problematic data were brought up by the data collection team
and corrected as necessary by reference to the relevant saved news documents. Given
that AMBER Alerts are by definition media events, it is very unlikely this data collec-
tion methodology, which involved building the dataset in real time as AMBER Alerts
were issued, would have missed any significant number of Alerts.2 We initially identi-
fied 630 total AMBER Alerts in the United States and Canada. After hoaxes, misun-
derstandings, child disappearances that turned out to not be abductions, and missing
data cases were eliminated, there were a total of 470 cases used in the analysis. Two
cases had two victims with two different outcomes, so those two cases were each
treated as involving two separate “AMBER Alerts,” bringing the operational N to 472.
Griffin et al. 7
An additional, unique strategy employed with these data was noting cases where
the content analysis of the available news coverage was consistent with a “Possible
Intimidation Effect.” In these particular cases, the data collection team determined it
was possible that awareness of the Alert induced the abductor(s) to release the children
unharmed but that was never directly stated in the news coverage. These “Possible
Intimidation Effect” cases should not be confused with “Intimidation Effect” cases
proper, where the content analysis provided clear evidence the abductor(s) surrendered
the child upon learning of the Alert. Thus, two versions of each statistical analysis are
conducted: one with the Possible Intimidation Effect cases treated as authentic
Intimidation Effect cases and thus, “successes,” and one where they were treated as
“no effect” cases. The goal is to provide a higher potential upper bound for the AMBER
Alert effectiveness rate, as well as an additional opportunity for AMBER Alerts to
show evidence of lifesaving or serious harm-preventing effectiveness. Both models
for each analysis are provided for the reader.
Dependent Variables
The dependent variables in the multivariate analyses are different measures of what
happened to the abducted children: Either Serious Harm (sexual assault and death) or
Any Harm (which encompasses any serious harm, as well as physical harm or injury).
Both are dichotomous (0 = no; 1 = yes.)
Independent Variables
Table 1 shows the descriptive statistics and coding protocols for the independent vari-
ables included in the analysis. The current study uses measures of predictive variables
similar to prior AMBER Alert research. The most important independent variable is
whether the AMBER Alert was a “success” or, as it will be reported in the findings,
whether the Alert had any “effect.” An Alert was deemed a “success” if the content
analysis indicated one of two “effects” occurred: (a) If a citizen, aware of the Alert,
observed the suspect and/or victim and informed police; (b) If a suspect became aware
of the Alert and surrendered the child to authorities or some other party—an
“Intimidation Effect.” (As indicated earlier, we provide analyses with and without
“Possible Intimidation Effect” cases treated as “successes.”) We iterate that the inde-
pendent variable of Alert Effect must not be confused with the dependent variable of
whether the child suffered any Harm. This again is because even though most children
in AMBER Alert cases are recovered unharmed, the Alert usually had nothing to do
with that safe recovery (see literature review).
The abductor’s relationship to the child is measured by a series of dichotomous
variables (0 = no; 1= yes) for: mother; father; other family member; boyfriend/girl-
friend; parent’s significant other; acquaintance; stranger; babysitter; car thief; both
parents together; internet acquaintance; unknown. Time delays between abduction and
alert (<3 hr), and abduction and recovery (<3 hr) are also dichotomous, (0 = no; 1 =
yes), as is gender. Age is continuous.
8 Criminal Justice Policy Review 00(0)
Finally, we measure “threat level” as categorical: Low threat (coded as 1) includes
cases involving no clear threat during the abduction; Medium threat (coded as 2)
includes cases where abductors were known drug abusers, had histories of mental ill-
ness, were intoxicated during the incident, were known to have a violent/abusive past,
made a threat of violence during the abduction, or demanded a ransom after the abduc-
tion. Medium threat also comprises cases where the child had a medical condition or
Table 1. Descriptive Statistics for Victim Harm, Alert Delay, Recovery and Effect, Abductor
to Victim Relationship, Victim Characteristics, and Abduction Threat Level (N = 472).
Variable XSD Min Max
Victim Harm
Any harm (0 = no; 1 = yes) .085 — 0 1
Serious harm (0 = no; 1 = yes) .068 — 0 1
Alert effect
Possible effect (0 = no; 1 = yes) .352 — 0 1
Real effect (0 = no; 1 = yes) .214 — 0 1
Delay and recovery
Alert delay < 3 hr (0 = no; 1 = yes) .544 — 0 1
Recovery delay < 3 hr (0 = no; 1 = yes)a.177 — 0 1
Abductor relationship
Mother (0 = no; 1 = yes) .396 — 0 1
Father (0 = no; 1 = yes) .216 — 0 1
Other family member (0 = no; 1 = yes) .059 — 0 1
Boyfriend/girlfriend (0 = no; 1 = yes) .032 — 0 1
Parent’s significant other (0 = no; 1 = yes) .040 — 0 1
Acquaintance (0 = no; 1 = yes) .066 — 0 1
Stranger (0 = no; 1 = yes) .034 — 0 1
Acquaintance/stranger (0 = no; 1 = yes) .100 — 0 1
Babysitter (0 = no; 1 = yes) .013 — 0 1
Car thief (0 = no; 1 = yes) .061 — 0 1
Parents together (0 = no; 1 = yes) .040 — 0 1
Unknown (0 = no; 1 = yes) .014 — 0 1
Internet acquaintance (0 = no; 1 = yes) .021 — 0 1
Victim characteristics
Female (0 = no; 1 = yes) .553 — 0 1
Age 5.11
Female > 9 years old (0 = no; 1 = yes) .146 — 0 1
Multiple victims (0 = no; 1 = yes) .186 — 0 1
Threat level
High threat (0 = no; 1 = yes) .381 — 0 1
Middle threat (0 = no; 1 = yes) .393 — 0 1
Low threat (0 = no; 1 = yes) .226 — 0 1
aN = 457 due to recovery delay not being calculated for children that were killed.
Griffin et al. 9
was abducted by noncustodial parents. High threat (coded as 3) includes cases involv-
ing disingenuous internet contact with underage victims an assault or murder during
the abduction, and those involving abductors engaged in unsavory romantic involve-
ments or. Our multivariate models also include the interaction term of female victim 9
years old or older. This measure is suggested by other prior research showing young
females are in fact disproportionately the target of harmful abduction situations, such
as those involving sexual assault and/or death (Hanfland et al., 1997).
Analytic Strategy
We first provide the basic descriptive statistics and coding protocols of the dataset to
give a general picture of the data and how they compare to prior reports and research
on AMBER Alert. Second, following prior literature (Griffin et al., 2016; Williams
et al., 2017), we construct logistic regression models to tease out the factors associated
with harm in AMBER Alert cases. These results shed light on (a), the general apparent
nature of AMBER Alerts in the sample and how they compare to earlier findings and
(b) the factors associated with AMBER Alert outcomes, allowing for an assessment of
the system’s utility in protecting children from harm in child abduction scenarios.
Third, we conducted difference of proportions tests to compare cases where there
was an AMBER Alert “success” (again, where the Alert had some “effect” in facilitat-
ing recovery either because of a citizen tip or the offender was intimidated into surren-
dering the child, and the child was returned unharmed) versus “safe-recovery-no-effect”
cases (again, where the Alert had no effect but the child[ren] were still recovered
unharmed). By thus comparing the “success” cases with the “safe-recovery-no-effect”
cases along all variables held in common, we are better able to determine whether sub-
stantive differences exist between the pools along known variables to shed light on how
they might or might not vary on the technically unknowable variable of actual “threat”
posed.
Results
Descriptive Statistics
The descriptive statistics in Table 1 are consistent with extant NCMEC annual sum-
maries and prior scholarly research on the attributes of AMBER alert cases, although
broad and exact comparisons across the datasets are not feasible owing to their exten-
sive differences. In 21% of the cases, the evidence from the content analyses of our
data suggested the Alert had some “effect” (and thus was a “success”—which again
overlaps with, but is distinct from, safe recovery). If the “Possible Intimidation Effect”
cases are treated as Intimidation Effect cases proper, the success rate in our data rises
to 35%. The relationship of the abductor(s) to the child(ren) is also consistent with
prior research, as the majority of the cases involved parents or other family members
(71%) and other categories of offenders not initially suggestive of clear threat.
Comparing our data with the NCMEC data is again extremely difficult because the
10 Criminal Justice Policy Review 00(0)
latter’s data involve very different variables, are entirely aggregated and organized by
year, and our data are coded down to the individual level and involve partial years (see
footnote 2). However, the 71% rate for familial abductions in our data is consistent
with the 65%, we calculated from the full NCMEC data years of 2012–2015, and for
those same NCMEC data years, we calculated the center’s reported percentage of
cases involving recovery within 3 hr after the child is reported missing to law enforce-
ment as 13%. This figure is roughly consistent with our percentage of cases involving
recovery within 3 hr after the abduction, which was under 18%. Time of abduction and
time of the report of a missing child are of course often different, and the NCMEC data
likely include the best possible estimates as ours often did, but the larger point is that
both datasets concur that recovery in AMBER Alert cases is not typically rapid.
Logistic Regression Model Results
Table 2 shows the results of the logistic regression models predicting the two outcome
variables: Any Harm or Serious Harm to the victims, with and without the Possible
Intimidation Effect cases counted among the “success” cases, or four models total.
Consistent with prior literature, the relationship between the abductor and the victim(s)
is by far the most robust predictor. For instance, in all four models, regardless of
whether Possible Intimidation Effect cases are counted as “successes,” the child is 6 to
nearly 8 times (ORs = 6.07–7.76) more likely to suffer any or serious harm when the
abductor or abductors are either strangers or acquaintances of the abducted children.
This also makes intuitive sense because it stands to reason abducted children are not
typically targets of intended harm in familial abductions. The correlation is not perfect
of course as there are in fact a handful of cases in the data where a family member
either seriously harmed or even killed the abducted child(ren). However, such cases
are very rare, which also makes sense in light of prior research on child abduction in
general showing that familial abduction cases almost never end in serious harm to the
children abducted (Sedlak et al., 2002).
Results further suggest that victim, offender, and contextual variables are also
significant predictors of eventual harm, again regardless of whether the Possible
Intimidation Effect cases are treated as “successes.” Females nine and older are nearly
four to five-and-half times (ORs = 3.95–5.47) more likely to suffer any or serious
harm. Also significant in all four models as a positive predictor of all measures of
harm is the variable of Collapsed Threat. This is both intuitive and an apparent vindi-
cation of the coding procedures. Offenders with indications of prior violence and or
sexual deviance were in fact more likely to inflict harm on the abducted children. For
each unit increase in potential or actual threat, the odds of suffering harm nearly dou-
ble. The presence of multiple child victims was a negative predictor in all four models
but was significant in none of them. We speculate that multiple-victim abductions
likely involve familial abductors less likely to inflict harm on the kidnapped children,
although again this variable approached but did not achieve significance. Rapid
AMBER Alert issuance (the AMBER Alert was issued within 3 hr of the abduction)
was not a significant predictor of any measure of harm in any of the four models. This
11
Table 2. Logistic Regression Results for Any Harm and Serious Harm, by Real or Possible Alert Effect (N = 472).
Treating possible intimidation effect cases as having “no effect”
Treating possible intimidation effect cases as having an “effect”
(“successes”)
Any harm Serious harm Any harm Serious harm
Predictor Variable b SE Odds ratio b SE Odds ratio b SE Odds ratio b SE Odds ratio
Perceived/actual threat level 0.681 (.263) 1.97* 0.750 (.305) 2.11* 0.775 (.269) 2.17** 0.846 (.310) 2.33**
Abductor a stranger/acquaintance 1.817 (.432) 6.15*** 2.049 (.465) 7.76*** 1.803 (.441) 6.07*** 2.024 (.472) 7.57***
Female victim 9-years-old or older 1.374 (.384) 3.95*** 1.698 (.419) 5.47*** 1.363 (.391) 3.91*** 1.693 (.425) 5.44***
Multiple children abducted −0.574 (.563) 0.56 −0.176 (.582) 0.84 −0.677 (.571) 0.51 −0.288 (.591) 0.75
Alert issued < 3 hr −0.035 (.365) 0.97 0.013 (.415) 1.01 0.031 (.370) 1.03 0.066 (.420) 1.09
Real alert effect −1.045 (.587) 0.35 −1.110 (.683) 0.33 — — — — — —
Possible alert effect — — — — — — −1.825 (.572) 0.16** −1.897 (.665) 0.15**
Constant −4.389 (.738) —*** −5.116 (.875) —*** −4.395 (.742) —*** −5.127 (.881) —***
*p < .05. **p < .01. ***p< .001.
12 Criminal Justice Policy Review 00(0)
is also consistent with prior research and strongly suggests official response time is not
a crucial factor in the determination of outcomes in Amber Alert cases.
Worth noting is that AMBER Alert Effect (again, where the Alert was a “success”)
is in fact negatively and significantly associated with Harm or Serious Harm, but
only when the Possible Intimidation Effect cases were counted as AMBER Alert
“Successes.” At first blush, this does seem to suggest AMBER Alert could be an
effective mechanism for reducing the likelihood of harm in child kidnapping cases
involving AMBER Alerts. However, two crucial questions are begged regarding this
finding. First, to what extent are the Possible Intimidation Effect cases, when treated
as “successes” involving an AMBER Alert “effect,” in essence mathematically
“borrowing” from the remaining “safe-recovery-no-effect” pool? This cannot be
known of course, since it is impossible to know which, if any, of the Possible
Intimidation Effect cases truly did involve Intimidation Effects proper, but it should
be a cautionary consideration before it can be assumed with certainty that the signifi-
cant finding for this variable suggests AMBER Alerts prevent harm.
The second question is also pertinent: Are children returned safely and unharmed in
AMBER Alert “success” cases because AMBER Alert prevented harm? Or does some
subset of AMBER Alerts have the opportunity to achieve an “effect” (and thus be
“successful”) simply because the abductors in those cases were never inclined to hurt
the children in the first place? Another way of thinking of it is to ask, is there any rea-
son to believe children in AMBER Alert “success” cases were in more danger than
children in AMBER Alert “safe-recovery-no-effect” cases who were also recovered
unharmed—but for reasons unrelated to AMBER Alert? Because if they were not, it
casts serious doubt on whether “successful” AMBER Alerts actually prevented harm.
It is to that matter we now turn.
Difference of Proportions Tests Comparing Effect (“Success”) Cases
With “Safe-Recovery-No-Effect” Cases
In an effort to shed light on these questions, we have also performed a partial replica-
tion of an earlier analytical strategy deployed in prior research on the effectiveness of
the AMBER Alert system (Griffin et al., 2016). We ran difference of proportion tests
comparing “success” cases (again, where the Alert had some “effect”) with “safe-
recovery-no-effect” cases (again, where the Alert had no effect but the victim[s] were
still recovered unharmed) to test the respective pools for any significant differences on
all other measured variables. As with the logistic regression models, we ran compari-
sons where Possible Intimidation Effect cases were treated as “successes” and models
where they were not. All cases in which the children were harmed were eliminated
because all such cases are by definition AMBER Alert “failures” if the child was
killed, and arguably at least partial “failures” if the children suffered nonlethal harm.
The logic of these difference of proportion tests is again to try to gain insight into
the problematic concept of “actual threat” posed in AMBER Alert cases. Neither we as
researchers nor officials engaged in the AMBER Alert issuance process can read the
Griffin et al. 13
minds of abductors in child abduction cases before or after the fact unless the abduc-
tion ends in murder or harm, in which case intentionality is tragically clear. As
researchers we have developed the crude estimation procedures explained above,
while AMBER Alert issuance authorities are forced to speculate about an abductor’s
intentions and the risk posed at the moment a particular missing child event is reported.
Table 3 presents the results of the difference of proportions tests. The results
strongly suggest that, regardless of whether Possible Intimidation Effect cases are
counted among them, “success” cases are highly comparable with the “safe-recovery-
no-effect” cases, as they are not significantly different on all but a few measured
factors. The comparability of the respective pools indirectly suggests they are likely,
on average, comparable along with other factors not directly measurable, such as the
elusive factor of perpetrator intention, or actual “threat.”3
A crucial point to keep in mind when considering these findings is that the differ-
ence of proportions tests conducted in this analysis examined only “success” and
“safe-recovery-no-effect” cases where all the child[ren] were returned unharmed. The
constant across the compared pools of no harm to the child already might speak to
something more profound than any statistical analysis. The children in both “success”
and “safe-recovery-no-effect” cases were not harmed, very arguably, because from the
onset, their abductors never intended to harm them, and whether the AMBER Alert in
a particular case had an effect or not is simply immaterial relative to the crucial factor
of perpetrator intention.
Discussion
Consistent with prior literature, the key variable predicting safe recovery in AMBER
Alert cases is Relationship. Strangers and acquaintances are more likely to harm chil-
dren in AMBER Alert cases; family members and other categories of offender, such as
babysitters and unknown car thieves, are less so. Furthermore, more rapid recovery
times are not associated with a lower likelihood of harm to abducted children in
AMBER Alert cases. We hasten to iterate our news media-derived data can shed no
direct light on the psychology of individual abductors. It is impossible to include vari-
ables such as “Murderous Intentions” or “Intending Sexual Assault.” Researchers, like
AMBER Alert issuing authorities deciding in short time frames with incomplete infor-
mation what constitutes “risk” in particular child abduction cases, are forced to use
proxy measures such as the relationship between the abductor and the children and
other factors mentioned in the news narratives, such as history of domestic violence,
drug abuse, or sexual deviance. Besides the “common sense” intuition most observers
would likely accept that mothers, fathers, grandparents, babysitters, aunts, uncles, and
similar abductors do not routinely pose physical threats to any children they might
abduct, survey evidence has (not surprisingly) confirmed that familial abductions
almost never end with the murder of the abducted children (Sedlak et al., 2002).
Despite the extensive media coverage of rare heinous cases, the overwhelming major-
ity of child abductions results from interfamilial feuds and custody disputes where the
children are caught between two familial factions, at least one and possibly both of
14
Table 3. Difference of Proportions Tests—Excluding Cases Involving Victim Harm (N = 443).
Treating possible intimidation effect cases as
having “no effect”
Treating possible intimidation effect cases as
having an “effect” (“successes”)
Compared Variable
Alert effect
(n = 101)
No alert effect
(n = 342)
Alert effect
(n = 166)
No alert effect
(n = 277)
Delay and recovery
Alert delay <3 hr .53 .56 .58 .53
Recovery delay <3 hr .18 .19 .18 .19
Abductor relationship
Mother .36 .43 .45 .39
Father .19 .24 .15 .28*
Other family member .07 .05 .06 .05
Boyfriend/girlfriend .01 .03 .02 .03
Parent’s significant other .03 .04 .04 .04
Acquaintance .09 .05 .07 .05
Stranger .04 .01* .02 .01
Acquaintance/stranger .13 .06* .09 .07
Babysitter .03 .01 .02 .01
Car thief .10 .06 .08 .06
Parent’s together .07 .04 .06 .04
Unknown .01 .01 .01 .01
Internet acquaintance .01 .02 .01 .02
Victim
Female .46 .55 .51 .54
Female > 9 years .10 .12 .10 .13
Multiple victims .17 .20 .18 .19
(continued)
15
Treating possible intimidation effect cases as
having “no effect”
Treating possible intimidation effect cases as
having an “effect” (“successes”)
Compared Variable
Alert effect
(n = 101)
No alert effect
(n = 342)
Alert effect
(n = 166)
No alert effect
(n = 277)
Threat level
No threat .30 .21 .23 .23
Known drug abuser .11 .12 .08 .13
Known violent past .05 .03 .05 .02*
Known sex offender .02 .03 .02 .03
Threat of violence .12 .09 .10 .09
Assault during abduction .15 .27* .27 .22
Murder during abduction .06 .07 .07 .07
Unsavory relationship .00 .01 .00 .02*
Child medical condition .02 .02 .01 .02
Ransom .00 .01 .00 .01
Disingenuous internet acquaintance .01 .01 .01 .01
Noncustodial parent .17 .15 .15 .15
High threat .20 .31* .30 .28
Middle threat .51 .48 .48 .49
Low threat .30 .21 .23 .23
*p < .05.
Table 3. (continued)
16 Criminal Justice Policy Review 00(0)
which involve unstable scofflaws, but they are unlikely to harm members of their own
family. It follows, again, there is no compelling evidence “successful” AMBER Alerts
constitute “rescues” from imminent harm in such cases.
To argue against this inference and suggest AMBER Alert deserves the benefit of
the doubt puts the system’s advocates and defenders in what appears to be a very awk-
ward position for multiple reasons. First, it groundlessly suggests AMBER Alert sys-
tem operators, who make issuance decisions in haste based on speculations about the
risk posed, are somehow uniquely privy to the psychological state of the abductors and
any environmental threats to the children relative to researchers with the benefit of
hindsight and under no time constraints when searching for evidence of the threat.
Second, it is empirically and logically incoherent to require proof of the negative that
AMBER Alerts do not work. The blanket claim that AMBER Alert “saves lives” or
“rescues” abducted children is not falsifiable, because no data exist on the psychologi-
cal states of abductors or the physical threats posed in particular cases. Third, and
related, is there a dangerous precedent set when crime control policies are granted
presumptions of effectiveness based on preference and hope absent any “proof” to the
contrary? If AMBER Alert enjoys this presumption, could not any array of policies
then be deemed “effective” in the absence of disproof?
To argue the system is nonetheless “worth it if it saves one life,” still runs into a
number of problems. First, there is the remaining open question of whether AMBER
Alerts have saved any lives, as it is again impossible to know what “would have” hap-
pened in any particular AMBER Alert “success” case had no Alert been issued.
Second, the argument that something is “worth it if it saves one life” can be applied to
anything—such as say, requiring all K-through-12 students to wear body armor to
improve their odds of survival in the event of a random school shooting (“Wouldn’t it
be worth it if it saves one life?”)—while ignoring any cost-benefit analysis of such
measures. Third and related, granting the system a pass based on hypothetical benefits
ignores its multiple unresolved potential deleterious effects, such as its potential for
swamping investigators with superfluous tips, placing system operators in impossible
issuance dilemmas set up to be second-guessed, manipulation of the system by savvy
offenders, the anecdotally suggested possibility of public attention pushing some
abductors to become unhinged and even more dangerous, and the distraction of public
attention from more pervasive threats to children (Griffin & Wiecko, 2015). To the
authors’ knowledge, none of these potential drawbacks of the AMBER Alert system
has been subjected to any empirical analysis.
Policy Implications
Although the results provided here are not promising for those hoping to see greater
evidence of AMBER Alert effectiveness at preventing harm to abducted children, they
are completely consistent with earlier findings in casting doubt on how much even
“successful” AMBER Alerts really accomplish. The findings might be especially more
poignant given they are derived from relatively recent data gathered after potential
improvements in system efficiency and the expansion of AMBER Alert into social
Griffin et al. 17
media. Thus, a number of potentially very important policy recommendations are sug-
gested by the findings presented here.
First, at this point, after a number of examinations of the effectiveness of the
AMBER alert system have failed to produce any compelling evidence the system pre-
vents harm to abducted children, it might be time for public officials to reflect on how
they discuss and portray AMBER Alert. As noted above, there is ample evidence
AMBER Alert enjoys a presumption of efficacy in preventing harm to abducted chil-
dren, but this is simply not supported by available data. We believe words such as
“rescue” and “lifesaving” are exaggerated at best, and it might be safer and more real-
istic to simply acknowledge the limits of the AMBER Alert system and what it can
actually accomplish. As has been pointed out, however, this might not be easy if the
system’s existence and public deployment serve the important function of “crime con-
trol theater,” enabling public safety officials to visibly and symbolically advertise their
commitment to addressing the emotionally loaded issue of child protection (Griffin &
Miller, 2008; and see Zgoba, 2004).
Another potentially very important implication of these findings, which public offi-
cials in general and AMBER Alert operators, in particular, might do well to consider,
is whether the AMBER Alert concept itself might suffer from unavoidable conceptual
flaws. As noted in previous research, there appears to be a very ambitious presumption
of how an AMBER Alert could actually prevent serious harm in a truly dangerous
child abduction scenario. Several very good things (nearly immediate official knowl-
edge of a kidnapping, rapid Alert issuance, and swift Alert effectiveness) need to occur
nearly simultaneously, and that could simply be unrealistic (Griffin & Miller, 2008).
Thus, a counterintuitive but possibly reasonable suggestion in light of these find-
ings is a reduction in the frequency of AMBER Alerts. System operators and designers
might consider the possibility that AMBER Alerts should only be issued where there
is an immediate knowledge of an abduction fitting one or more known high-risk tem-
plates (e.g., any time a female is abducted by a nonfamilial male), and where there is
immediately usable information that could help the general public tangibly assist law
enforcement. The argument for this approach is twofold. First of all, in situations
where the information is poor and the possibility of rapid response is minimal, the
AMBER Alert is unlikely to accomplish anything normal law enforcement would not
accomplish anyway. Second, by limiting AMBER Alert issuances to these “clear-cut”
cases, it gives the system the best chance to actually demonstrate “rescues” or even
“lifesaving” success—if that is possible.
This suggestion, however, introduces its own potential problems. The first system-
atic examination of the AMBER Alert system (Hargrove, 2005) made a recommenda-
tion essentially identical to the one just proposed in this paper: AMBER Alerts should
be restricted to serious cases instead of the familial and other apparently “trivial” situ-
ations where they were typically deployed. But the problem here is the cases the author
of that early study deemed “trivial” were only known with certainty to be such after
the fact, and how can issuing authorities be faulted for “erring on the side of caution”
in such cases if they operate under the assumption an AMBER Alert could make a
difference?
18 Criminal Justice Policy Review 00(0)
Establishing a more restrictive bar for AMBER Alert issuance also runs into poten-
tial political trouble. Suppose, for the sake of argument, a revamped issuance rule is to
never issue Alerts if more than 3 hr have passed since the last time a missing child was
seen since if the case is truly life-threatening, research has shown any window of
opportunity has probably passed (Brown et al., 2006; Hanfland et al., 1997).4 The
problem here is that failure to issue AMBER Alerts in controversial cases has often
resulted in bitter backlash (from citizens who have been led to believe AMBER Alerts
“rescue” abduction victims) against public safety officials for seemingly devaluing
some missing children (Griffin & Wiecko, 2015).
Therefore, any attempt to make the issuing criteria more restrictive would have to
be accompanied by a more realistic public discourse about AMBER Alert effective-
ness. Public safety officials and system operators would need to embrace and acknowl-
edge the findings of this and prior research about the system’s apparent limits. They
would have to start disseminating the disheartening messages that (a) the system usu-
ally contributes nothing when deployed and (2) even when it does contribute some-
thing it is rarely if ever in menacing cases. To date, they have been reluctant to do that,
again possibly because the AMBER Alert system’s very existence is a powerful sym-
bol, if nothing else, of official commitment to child safety (Griffin & Miller, 2008).
Nonetheless, perhaps this bitter bill should be swallowed because as has been noted in
prior research, the inflated expectations of the system are likely responsible for public
outcry when the “silver bullet” of AMBER Alert is not deployed in cases that end hor-
ribly (Griffin & Wiecko, 2015). Thus, more realistic discourse and more restrictive
issuing criteria might go hand in hand in considering the future of the AMBER Alert
system.
Another possibly very important policy implication to emerge from these and other
findings is the overall importance of what AMBER Alert symbolizes in terms of social
priorities invested in threats to children. Although the AMBER Alert system is actually
a very small part of overall American crime control inasmuch as it involves only a few
hundred offenders and victims in any given year, its symbolic importance cannot be
overstated. If social resources and investigative attention are disproportionately
invested in a handful of cases deemed worthy of an AMBER Alert, then a diminished
focus on the vast majority of threats to children is a very plausible outcome.
All of this was in fact anticipated in an early examination of the system’s political
origins, where Zgoba (2004) argued the AMBER Alert system, inspired by moral
panic over the legitimate but socially distorted goal of child safety, was hastily created
and ultimately implemented nationwide by the 2003 federal PROTECT act without
serious reflection on its likely empirical, conceptual, and policy discourse problems.
Zgoba’s concerns at this point appear to have been prophetic, which invariably leads
to yet another consideration. AMBER Alert could be a symbol, not just of misdirected
social attention concerning endangered children specifically, but of how crime control
policies are generally conceived, implemented, and regarded in larger American
society.
This could be called the “AMBER Alert heuristic.” AMBER alert is by definition
an attention-getter, and it could be time to consider it emblematic of larger
Griffin et al. 19
dysfunctions in how crime control policy is conceived and implemented in the United
States. Do symbolic policies enjoy a presumption of efficacy in the absence of com-
pelling evidence precisely because of their visceral appeal? This again is the problem
of “crime control theater” (Griffin & Miller, 2008), of which AMBER Alert is, at least
based on the available evidence, a profound example (Miller et al., 2018; Sicafuse &
Miller, 2010).
Conclusion
This article used data gathered from media accounts of a sample of relatively recent
AMBER Alerts issued in the United States from 2012 to 2015. Basic descriptive sta-
tistics, logistic regression analyses to determine the drivers of safe recovery, and dif-
ference of proportions tests comparing “success” versus “safe-recovery-no-effect”
cases yielded results very similar to available prior research on the AMBER Alert
system. Most Alerts have no effect, perpetrator identity (and not system efficiency)
appears to be the primary determinant of safe recovery, and “success” and “safe-recov-
ery-no-effect” cases are largely comparable to each other on measurable attributes,
strongly suggesting they are also comparable on the technically unknowable variable
of the threat posed. This in turn suggests “successful” AMBER Alerts are not likely
“rescuing” children from imminent harm.
These results buttress earlier findings that the AMBER Alert system is being over-
sold to the public, and a more tempered assessment of the system and even restruc-
tured issuing criteria are suggested. The findings also indicate that, as a likely example
of “crime control theater,” the AMBER Alert system has significant lessons for the
general public and policymakers about how policies to aid imperiled children in par-
ticular and crime control policies, in general, are assessed and discussed.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship,
and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of
this article.
ORCID iDs
Timothy Griffin https://orcid.org/0000-0002-7426-4434
Joshua H. Williams https://orcid.org/0000-0003-3280-4268
Notes
1. Several changes have expanded the visibility of AMBER Alerts onto social media. In
2011, AMBER Alert Facebook pages at the state and national levels were created. In 2012,
Google added AMBER alerts to their search engine and Public Alerts service. In December
20 Criminal Justice Policy Review 00(0)
2012, the Wireless Emergency Alerts system was used to send an Amber Alert. In 2015,
Google Adds AMBER Alerts into the traffic app, Waze, and Facebook “expands their
AMBER Alert resources and begins pushing alerts to people near the area where the child
went missing,” (U.S. Department of Justice, Office of Justice Programs, 2021c).
2. An anonymous reviewer suggested we provide a validation of this claim specifically and
about data quality in general, and thus we compared our media-based dataset with the offi-
cial National Center for Missing and Exploited Children (NCMEC) statistics for our data
collection window. The comparison was problematic, as NCMEC reports do not provide
individual-level case data that would enable direct comparison with our media-derived
dataset, and do not disaggregate certain fields by month, which would be necessary for
us to precisely compare our partial data collection years of 2012 and 2015 to the NCMEC
reports. Nonetheless, through a meticulous counting and estimation procedure based on
the available NCMEC information on U.S. AMBER Alerts, and taking into account our
20 Canadian AMBER Alerts, we estimated we “should have” identified 640 total AMBER
Alert cases, whereas we had 630. Errors in our estimation procedures with the NCMEC
data, and possibly a few omissions in the Google News Search data collection method,
probably explain the observed difference. Furthermore, since our analysis only looks at
AMBER Alerts involving an actual abduction, and not hoaxes and runaways and other
non-abduction categories, we further used the NCMEC data to estimate we “should have”
had 496 actual abduction AMBER Alert cases, whereas we only used 470 in our analy-
sis. The difference of 26, however, is almost perfectly explained by our 27 missing-data
cases from our “actual abduction” pool—possibly in concert with potential errors similar
to those described above for the total case count. Thus, we are confident our data triangu-
late very well with the NCMEC numbers. A more detailed explanation of the comparison
procedure is available from the corresponding author upon request. The authors can also
provide further information on the coding protocols, the data inputting and cleaning proce-
dures, and (most important) a systematic random subsample of the cases based on a starting
point (the cases were assigned numbers successively as they emerged from the news alerts)
chosen by the inquirer upon request.
3. Nonetheless, it should be noted there are significant differences on a few variables depend-
ing on the models examined. For example, in the comparison treating Possible Intimidation
Effect cases as “no effect” cases, AMBER Alert cases where the alert had an effect were
more likely to involve Strangers (and the related variable of Stranger or Acquaintance).
AMBER Alert Effect cases were significantly less likely to involve an Assault during the
abduction but, ironically, the highest level of Threat.
These findings could merely reflect statistical noise because so many variables were com-
pared across the two pools of case types in all models. Furthermore, when the Possible
Intimidation effect cases are included in the difference of proportions tests, these find-
ings disappear and yet another trio of variables (whether the abductor was the father of
the abducted children, whether the abductor had a known violent past, and whether the
circumstances of the abduction involved an illegal involvement with an underage victim)
appeared as significant. This lends some credence to the statistical noise inference, as com-
paring enough variables across the respective pools could trigger significant findings just
by chance, and those chance findings could just differ randomly based on how “Possible
Intimidation Effect” cases are treated.
4. Brown and Keppel (2007) found that the time elapsed between initial contact and eventual
homicide was <5 hr in 85% of child abduction murders.
Griffin et al. 21
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Author Biographies
Timothy Griffin is an associate professor of criminal justice at the University of Nevada, Reno.
His diverse research interests include the AMBER Alert system, public discourse in crime
policy, and public crime policy.
Joshua H. Williams is a senior research associate with VK Strategies. He earned his PhD from
the University of Missouri—St. Louis in 2018. His current research interests include bail and
pretrial detention, politics and punishment, community context and sentencing, and criminal
justice policy.
Colleen Kadleck is an associate professor in the School of Criminology and Criminal Justice at
the University of Nebraska Omaha. Her current research interests include policing, representa-
tions of crime and justice, and policy.