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ARCHEOLOGY OF EXCLUSION: COUNTER-MAPPING SITES OF EXCLUSION AND OPPRESSION IN THE ADMINISTRATIVE STATE USING GIS.

INTRODUCTION

In public administration, research on geographic information systems (GIS)--i.e., "computer hardware, software, and geographic data designed to efficiently capture, store, update, manipulate, analyze, model, and display all forms of geographically references information" (Vonk, Geertman, & Schot, 2007, p. 745)--has been limited to studies about: 1) The diffusion, use, and implementation of GIS in the public sector (Brown & Brudney, 1998; Brown, O'Toole, & Brudney, 1998; Nedovic-Budic & Godschalk, 1996; O'Looney, 2000; Ventura, 1995; Vonk et al., 2007); 2) The role of GIS in the field's curricula (Obermeyer, Ramasubramanian, & Warnecke, 2016); And 3) public participation geographic information systems (PPGIS) (Ganapati, 2011; Haque, 2001). In terms of (1) public sector applications, Haque (2001) and Obermeyer et al. (2016) note that GIS is used for planning and community development, the delivery of daily and emergency services, infrastructure management, monitoring the spread of infectious diseases, transportation planning and modeling, assisting in redrawing voting and school districts, and much more. As a matter of (2) teaching, Obermeyer et al. (2016) find that while there is a demand for graduates competent in GIS, public administration programs have not met this need. Finally, concerning (3) PPGIS, given that the goal of PPGIS is to empower communities and, effectively, increase democracy (Ganapati, 2011; Sieber, 2006), it is readily compatible with many of the American Society for Public Administration's (ASPA) and the Network of Schools of Public Policy, Affairs, and Administration's (NAASPA) core values. This is all to say that the future of GIS scholarship in public administration is full of promise and, as the field's GIS archive matures, it will probably be grounded in these three topics.

However, missing from public administration's GIS research agenda is a critical look at GIS. Like any other tool of public policy (Salamon, 2002), geographic information systems do not exist in a-political, or neutral, vacuums. Instead, GIS is a tool that, like others, can be manipulated. Although the topic is practically absent from the field's GIS archive, critical GIS has a rich genealogy in the field of geography (see O'Sullivan, 2006; Schuurman, 2006; Sheppard, 2005). For the purposes of this discussion, critical GIS is, as Sheppard (2005) understands it, a research program that rose to challenge GIS' positivism, inaccessibility, and failure to accommodate marginalized voices (see Schuurman, 2006, p. 727). Within this research program there are what Peluso (1995) calls counter-maps, i.e., alternative maps that challenge the status quo. While PPGIS--which is already part of public administration's research agenda--and critical GIS share raisons d'etre, the introduction of critical GIS to public administration opens doors to new areas of inquiry beyond issues of public participation, such as social theory, equity, justice, and philosophy vis-a-vis GIS.

As public administration continues to explore geographic information systems as both a tool of public policy and a topic of interest, the field needs to take critical GIS seriously. If, as Frederickson (2005) argues, in carrying out laws and policies, public servants face "important struggles with fairness, justice, and equality" (p. 32), then it behooves administrators to understand the power dynamics that foment exclusion and undermine democratic values in the administrative state; a task that critical GIS is well-suited for. To effectively fulfill their duty, public administrators need to embrace their role as de facto arbiters of conflict and champions of democracy (Nabatchi, Goerdel, & Peffer, 2011). Herein, I argue that critical GIS can help public administration scholars and practitioners engage counter-narratives through counter-maps that portray sites of exclusion, which has significant implications for a socially just administrative state emboldened by a democratic ethos. To do so, I start with a conceptual discussion about the role of exclusion and oppression in the administrative state by way of Agamben's (1998; 2004) state of exception, Kristeva's (1982) notions of the abject, and Quijano's (1992; 2000) coloniality of power thesis. Thereafter, I offer examples of exclusion and oppression in praxis. This is followed by a case study that looks at the shooting of seventeen-year-old Trayvon Martin in Sanford, Florida, on the evening of February 26, 2012. To supplement the study, I used ArcMAP 10.5.1 to geocode Florida's 2010 and 2015 American Community Survey (ACS) five-year estimates at the block-group level. Then, I used Stata 15.0 to run confirmatory factory analyses (CFA). Lastly, I exported the linear factor scores to ArcMAP to create a series of choropleth counter-maps. These counter-maps unearth a series of inequalities that, quite possibly, empowered George Zimmerman's choice to remove Trayvon Martin from a place where Trayvon's presence was the exception. Finally, this is not intended to be, nor can it be, an examination of all the factors that contributed to the killing of Trayvon. Rather, this is an attempt to use GIS to talk about why individuals, like Zimmerman, may feel justified to make decisions about who belongs and does not belong on behalf of the public. Broadly speaking, this is a project to excavate the roots of exclusion and oppression that empower violence against another on behalf of the public--an archeology of exclusion in the administrative state.

ARCHEOLOGY OF EXCLUSION

The following section establishes the state of exception as a reaction to abnormalities in the administrative state (Agamben, 1998; 2004; Schmitt, 1922/2005). This reaction, as Kristeva (1982) posits, is a matter of abjection (i.e., a self-defining decision to cast out that which cannot, or does not, belong). In doing so, abjection is a means to continually define and redefine the limits and meaning of membership. The introduction of Quijano's (1992; 2000) coloniality of power thesis gives context to the state of exception. Accordingly, the modern state of exception in the Americas was originally used to claim supremacy over non-European peoples. The colonial apparatus, as Quijano (1992; 2000) argues, required the systematic dehumanization of non-Europeans in conjunction with the implementation of systems of cultural, economic, and social oppression to keep marginalized peoples away from privileged spaces. Per Quijano (1992; 2000), this perspective is important because these dynamics of dehumanization and oppression continue to operate today. As such, it is possible to comprehend the contemporary state of exception by using indicators of cultural, economic, and social oppression to counter-map tensions across communities. While this is not a formal archeology (i.e., a study of past civilizations), the conversation is inspired by Foucault's (1969) use of archeology to unearth rules that dictate ontological boundaries. Moreover, my aim here is to excavate new insights about the roots of exclusion and mechanisms of oppression in the administrative state.

The State of Exception

Agamben's (1998) notion of the state of exception is a useful starting point to understand the role of exclusion in the administrative state. At the crux of Agamben's (1998) concept is the suggestion that rootedness (i.e., a sense of place) necessitates normativity. Similarly, regarding jurisprudence, Schmitt (1922/2005) points out that the administration and implementation of law(s) demands a normal order. This is because abnormal conditions render judicial outcomes uncertain, especially during crises. Hence, during abnormal times, judicial order should be suspended to effectively return to normal (Schmitt, 1922/2005). In other words, abnormality is addressed by instituting a state of exception to laws that would otherwise operate haphazardly. Logically, the concept calls for a polity to make the decision to institute a state of exception; a decision imbued with power, which is why Schmitt (1922/2005) defines the sovereign as "he who decides on the exception" (p. 5). Per Schmitt (1922/2005), the rule of law depends on a sovereign's power to enact a state of exception during a crisis; a decision that in a democracy should be made on behalf of the People (or the will of the People). Now, whereas Schmitt (1922/2015) outlines the state of exception as a condition of possibility for an enduring administrative state, Agamben (1998) shifts the conversation from jurisprudence to the concept's ontological limits. In a sense, to exclude is to possess the power to define and redefine the limits of existence--of belonging and nonbelonging--by articulating and rearticulating exceptions to presumed normal life. The exception begets a sense of belonging-through-exclusion to the extent that people fathom their sense of belonging only in relation to the excepted/excluded Other. So, when there is a need to understand the limits of membership (or belongingness)--or when membership is contested--the declaration of a state of exception helps to articulate and cast out that which does not or cannot belong. Ultimately, in line with Agamben (1998), the state of exception is as much a suppression of law as it is a suppression of life. Taken to the extreme, a real-life consequence of the declaration of a state of exception is the forcible relocation of exempted peoples to sites of exclusion--Agamben (1998) points to the Nazi concentration camps as prototypes of this process.

At the margins of the state of exception lies the threshold: a zone of indistinction wherein the quintessential uniqueness of membership, albeit artificial, is asserted through its witnessing of the exception (Agamben, 2004). The zone of indistinction is where the rule and the exception, normal and abnormal, come face-to-face. Since the zone of indistinction (sometimes a fence, sometimes a wall) needs to change as it encounters a new abnormal, the threshold can be understood as "only a place of ceaselessly updated decision in which the caesurae and their rearticulation are always dislocated and displaced anew" (Agamben, 2004, p. 38). Overall, the state of exception is a recursive formation or an event from which the exception and the rule emerge and reemerge as prerequisites for belonging and nonbelonging. Arguably, per Schmitt (1922/2005), the administrative state necessitates the declaration of a state of exception, made on behalf of the People. However, as Catlaw (2007) ascertains, the People is a symbol used to perpetuate a sense of unity at the expense of differences. To be a People, to belong, is to "exist as a truncated being, denying or erasing all aspects of self" that do not belong (Love, 2013, p. 577). What is left behind is life without rootedness, life repeatedly reminded of its abnormal status, "life exposed to death" at the hands of sovereign violence, life made bare life (Agamben, 1998; see also Catlaw & Holland, 2012).

Abjection

Without a doubt, to understand the state of exception in the administrative state, one must understand the state's relationship with what it essentially proclaims disgusting--that which threatens to undermine the rule or normative order (Patterson, 2001). Kristeva (1982) explains that abjection, i.e., the expulsion of the abject (an aberration to the rule), is a strategy to assert the self and by extension assert a sense of belonging and membership. While this corroborates the underlying logic of the state of exception, Kristeva (1982) takes the concept further by noting that abjection is "above all ambiguity. Because, while releasing a hold, it does not radically cut off the subject from what threatens it--on the contrary, abjection acknowledges [the subject] to be in perpetual danger" (Kristeva, 1982, p. 9). This notion of perpetual danger alludes to the precarious subject-position of belonging, it points to a fragile sense of membership, and it vindicates the relentless, inherently Sisyphean, affirmation and reaffirmation of legitimacy. At its core, the administrative state's sense of self is artificial, yet, it refuses to acknowledge its own artificiality and cleaves for legitimacy. By claiming legitimacy, the administrative state refuses to change. In effect, it tries to overcome its identity crisis--its underlying illegitimacy--by portraying itself as a unique and constant entity (not surprisingly, this phenomenon is not unheard of in public administration, for a discussion see Moura & Miller, 2016). In terms of individual livelihood, belonging to/in the administrative state means that life is diluted because people are expected to perform norms (e.g., gender, see Butler, 1988) that delimit their being-in-the-world (in short, their possibilities). Refusal--which would constitute an aberration to the established normative order--begets abjection and bare life.

Coloniality of Power

Herein, the focus has been on the state of exception as a condition of possibility for an enduring administrative state (Schmitt, 1922/2005); a condition that, as Agamben (1998) theorizes, can lead to the forcible expulsion, or abjection (Kristeva, 1982), of anOther. Missing from the discussion is a look at the conditions that substantiate the sovereign decision to render bare life within the administrative state, with special attention to the Americas. In other words, what are the conditions that validate, if not incite, the declaration of a state of exception and sovereign violence in modern American times? Quijano (1992; 2000) approximates an answer by acknowledging that one of the most destructive byproducts of modernity was the Cartesian mind/body split. Cartesian dualism, as Quijano (2000) elaborates, presumed that reason was not contingent on the body. It followed that possession of a corporeal body was not enough to claim humanity. Instead, a human had to be reasonable by Western standards. As such, Cartesian dualism fueled a modern anthropological machine--a machine that lives on in the contemporary administrative state (see Catlaw & Holland, 2012)--that "functions by excluding as not (yet) human an already human being from itself, that is, by animalizing the human, by isolating the nonhuman within the human" (Agamben, 2004, p. 37). Throughout the colonial period, Cartesian dualism justified the declaration of a state of exception against non-Europeans, who, because they were different could be stripped of (or denied) their humanity. This, in turn, warranted the systematic oppression and ongoing dehumanization of non-European peoples. Effectively, this process facilitated European usurpation, violation of indigenous rights, resource exploitation, and the subjugation of the Other.

In the Americas, the systematic oppression and dehumanization of the Other, as Quijano (2000) explains, was manifest in the intersection of: race structures that sanctioned White supremacy (for a discussion see Heckler, 2017, pp. 176-178); gender structures that accepted European men as rational actors and women as insensible objects; systems of sexuality that enforced heterosexism (Lugones, 2007); systems of economic oppression that afforded salaried labor to the colonizer and low wages, if not servitude, to the colonized (all on behalf of an emerging capitalist structure--as an aside, this also has important implications for economic rationalism in public administration, see Alkadry & Blessett, 2010); and systems of cultural oppression and erasure that imposed European epistemic and ontological values as objective Truths over non-European beliefs (see Mignolo, 2007). When colonialism ended, its coloniality forged ahead via these axes of power. Today the status quo and the power to protect it are the birthright of the oppressor. Here, Clark's (1965) observations about the American dark ghetto are illustrative:
The dark ghetto's invisible walls have been erected by the white
society, by those who have power, both to confine those who have no
power and to perpetuate their powerlessness. The dark ghettos are
social, political, educational, and--above all--economic colonies.
Their inhabitants are subject peoples, victims of the greed, cruelty,
insensitivity, guilt, and fear of their masters [emphasis in original].
(p. 11)


Clark's (1965) comments showcase zones of indistinction (invisible walls) that effectively separate White society (the People) from the subject peoples (the abject). The ghetto (a state of exception) is a place of oppression, a colony founded on social, political, educational, and economic inequity. These systems (axes of power) safeguard the masters' hegemony and beget the subject peoples' sense of worthlessness (bare life)

THE STATE OF EXCEPTION AND PRAXIS

Borderlands

As a matter of public policy in the American administrative state, the threshold and the state of exception are oftentimes quite visible. For example, post-9/11, the Fence Act of 2006 mandated the construction of an 18-feet-high fence on the US-Mexico border, alongside the Rio Grande, to protect the US from unlawful intrusion. Garrett and Storbeck (2011) argue that this fence enacted a "new 'other space'... based on the notion of a state of exception, facilitating the displacement of people living along the lower Rio Grande" (p. 542). The enactment of the Fence Act--a declaration of a state of exception--created a new space as the zone of indistinction changed to cope with the need to secure American borders from external threats. When the threshold moved, property owners and communities in proximity to the border had to acquiesce and perform accordingly. Similarly, President Trump's wall proposal (i.e., an 18- to 30-feet-high wall) is yet another example of declaring a state of exception to redefine the limits of membership. If built, President Trump's wall will once again shift the zone of indistinction to find a sense of place--to "make America great again"--at the expense of Others. Over a decade prior to these actions, the Chinese Exclusion Act of 1882 also used the rhetoric of undesirability to abject Chinese immigrants. The same rhetoric was used in the Johnson-Reed Act of 1924, which, as Ngai (2004) clarifies, employed a restrictive system of comprehensive quotas on immigrations and started a period of mass deportation and surveillance. In doing so, Ngai (2004) contends that "immigration policy rearticulated the U.S.Mexican border as a cultural and racial boundary, [and] as creator of illegal immigration" (p. 67). Although these examples are not meant to be an exhaustive historiography, they should further highlight an American tradition of exclusion with very real social consequences.

Migration policies offer concrete illustrations of the state of exception because borderlands are a permanent and unambiguous state of exception (Salter, 2008). Yet, zones of indistinction, to borrow Clark's (1965) phrase, can be invisible walls. This is not to say that case studies of the borderland do not generate meaningful knowledge. On the contrary, Garret and Storbeck's (2011) study offers important insights into the lived-realities of Brownsville residents vis-a-vis the Fence Act of 2006. Likewise, Pope and Garrett's (2012) study of Arizona's SB 1070 (a restrictive 2010 anti-immigrant law) highlights the abjection of Latinos living in Arizona. Nevertheless, to focus solely on the borderland is to ignore the reiterations of the exception--the oppression and dehumanization of the Other--just as it is to sidestep candid conversations about the politics of exclusion and the coloniality of power in other contexts. Fundamentally, since one of the defining features of the administrative state is the exception, abjection is not only a borderland issue, it is also a civil rights issue. To truly embrace a democratic ethos, extant public administrators need to also consider the systems of exclusion and abjection present in communities beyond the borderland.

The Public Servant

The declaration of a state of exception and the forcible abjection of the Other safeguards normativity. Moreover, the coloniality of power protects Western hegemony through systems of dehumanization. In turn, these systems of dehumanization erect invisible walls, zones of indistinction, that delimit the agency of abject subjects. Apropos, in postcolonial United States, as Blessett (2015) observes, Whites (the People) have retained the "authority and resources to create policies, influence the economic and political decisions that govern the country, and shape the images of people and places as worthy and deserving or dependent and deviant" (p. 9). That is, Whites, as inheritors of colonial power, possess the authority and resources to define and redefine the limits of membership insofar as belonging is reserved for the worthy and abjection is reserved for the deviant. This alludes to a critical issue: in and of itself, the administrative state does not act, public administrators act. By being a representative of the state (the People), the administrator can use discretion to decide on the exception. In line with Schmitt's (1922/2005) notion of the state of exception, the public servant should use this power to uphold the will of the People. Yet, in line with Agamben (1998), the power to decide on the exception can easily lead to the justified displacement of anOther and the creation of bare life. Not surprisingly, Alkadry and Blessett (2010) share that American public administrators, like British imperialist functionaries, have used "bureaucracy, racism, and violence . to force African Americans into submissive roles" (Alkadry & Blessett, 2010, p. 552). Since public servants have access to the sovereign power to decide on the exception, there is a need to understand how abjection influences their decisions.

"It's Raining and He's Just Walking Around, Looking About"

Per Table 1, if the public administrator is X and the abject is Y, what are the constraints that the public administrator (X) enforces to make the presumed abject (Y) yield to the status quo? More importantly, if the abject (Y) refuses, is the public administrator (X) justified to declare a state of exception and, quite possibly, use violence to remove the abject (Y)? Answers to these questions are less about policies of exclusion and more about street-level decision-making and the implementation of dehumanization and oppression.

Germane to this discussion, George Zimmerman's decision to pursue and kill Trayvon Martin tragically underscores the violent repercussions of the street-level state of exception. The killing of seventeen-year-old Trayvon Martin in Sanford, Florida, on February 26, 2012, has been reviewed in terms of race, Stand Your Ground Laws, structural racism, and public outrage (Barry, Kovaleski, Robertson, & Alvarez, 2012, April 1; Lawson, 2012; Lee, 2013). However, it is also possible to see the shooting of Trayvon as a matter of people, whether they are officially appointed or simply think that they act on behalf of the state, deciding on the exception. Coming back from a 7-Eleven, Trayvon caught the attention of the then twenty-eight-year-old George Zimmerman, a neighborhood watch coordinator for the Retreat at Twin Lakes gated community (Barry et al., 2012, April 1). Upon seeing Trayvon, Zimmerman (n.d.) dialed 911 and told the dispatcher:
Zimmerman: Hey we've had some break-ins in my neighborhood, and there's
a real suspicious guy, uh, [near] Retreat View Circle... This guy
looks like he's up to no good, or he's on drugs or something. It's
raining and he's just walking around, looking about.
Dispatcher: OK, and this guy is he white, black, or Hispanic?
Zimmerman: He looks black.
Dispatcher: Did you see what he was wearing?
Zimmerman: Yeah. A dark hoodie, like a grey hoodie, and either jeans or
sweatpants and white tennis shoes. He's [unintelligible], he was just
staring...
Dispatcher: OK, he's just walking around the area...
Zimmerman:... looking at all the houses.


Considering recent break-ins throughout "[his] neighborhood," Zimmerman suspects that Trayvon is "up to no good." According to Zimmerman, there is something uncanny about Trayvon's behavior because the young man should not be walking and looking around in the rain. Here, the subtext is that no normal person would do these things unless they were "up to no good" and "on drugs or something." As mentioned, Zimmerman's reaction was to call the police and, in doing so, he had already decided that Trayvon did not belong in "[his] neighborhood." The 911 call continues:
Dispatcher: OK...
Zimmerman: Now he's just staring at me.
Dispatcher: OK-- you said it's 1111 Retreat View? Or 111?
Zimmerman: That's the clubhouse...
Dispatcher: . [H]e's near the clubhouse right now?
Zimmerman: Yeah, now he's coming towards me.
Dispatcher: OK.
Zimmerman: He's got his hand in his waistband. And he's a black male.
Dispatcher: How old would you say he looks?
Zimmerman: He's got button on his shirt, late teens.
Dispatcher: Late teens, OK.
Zimmerman: Something's wrong with him. Yup, he's coming to check me
out, he's got something in his hands, I don't know what his deal is.
(Zimmerman, n.d.)


Since Trayvon cannot belong, Zimmerman refuses to see him as a reasonable actor. He thinks that Trayvon is aberrant because he is walking outside while it is raining but fails to acknowledge that Trayvon's decision to wear a hoodie is a reasonable preemptive act against the rain. He thinks Trayvon is abnormal because "he's just staring at [him]" and "coming towards [him]" but does not acknowledge Trayvon's behavior mirrors his own, i.e., Zimmerman is also staring and following. He thinks that there is "something wrong with [Trayvon]" because Trayvon "is coming to check [him] out" but does not acknowledge that he is doing the exact same thing, checking Trayvon out. Finally, he thinks Trayvon is strange because "he's got something in his hands," but does not acknowledge that he is also holding something in his hands, a cellphone. At this point, because Zimmerman believes Trayvon is the abject, the young man is denied reason. He is not permitted to act like Zimmerman.
Dispatcher: Just let me know if he does anything, OK?
Zimmerman: How long until you get an officer over here?
Dispatcher: Yeah, we've got someone on the way, just let me know if
this guy does anything else.
Zimmerman: Okay. These assholes they always get away.
[...]
Zimmerman:... Shit, he's running.
Dispatcher: He's running? Which way is he running?
[...]
Dispatcher: Are you following him?
Zimmerman: Yeah.
Dispatcher: Ok, we don't need you to do that. (Zimmerman, n.d.)


Throughout the call, Zimmerman's intention is to establish why Trayvon, like the "assholes [that] always get away," needs to be escorted out by law--ergo, his request for an officer. It is implied that to return to the normal order, Trayvon needs to be excluded. Also, it is noteworthy that, during the call, the Dispatcher's main priority is to develop a profile of Trayvon (most likely to ensure an officer readily identifies him), instead of asking Zimmerman why Trayvon's benign behavior is so disturbing. When Trayvon starts to run away from Zimmerman, the Dispatcher articulates that "we don't need you [Zimmerman] to do that." This statement is problematic because it leaves room for discretion; while "they" do not "need" Zimmerman to pursue Trayvon, this is not a command against following the adolescent. Rather, Zimmerman is given the choice to wait and meet the police officer, which is the focus of the rest of the call (not shown here), or ensure Trayvon is caught and exempted by force.

Sadly, Zimmerman chose the latter and, at 7:17 pm, he shot and killed Trayvon Martin--Trayvon was holding a bag of skittles and iced tea. Although Sanford Police arrested him, Zimmerman claimed self-defense and was subsequently released under Florida's Stand Your Ground Law and later acquitted. Why did Zimmerman make the choice to pursue Trayvon? Why was Trayvon's presence so alarming to Zimmerman's presumed normal order? Using GIS, it is possible to show tensions in Sanford that, quite possibly, contributed to Zimmerman's choice.

CRITICAL GIS

As shown in Table 1, the normal order thrives due to the coloniality of power because its systems of oppression guarantee the ongoing dehumanization of colonial subjects (e.g., African Americans and indigenous peoples in the United States). In doing so, this process foments power imbalances across communities whereby beneficiaries of the status quo have cultural, economic, and social affluence while abject communities are left at a disadvantage--a point reminiscent of Massey's (1996) assertion that the juxtaposition of extreme affluence and disadvantage in American cities "stems from deep powerful forces operating in the world today" (p. 399). If the normal order is operationalized as cultural, economic, and social affluence and disadvantage, then it is possible to use critical GIS to map power imbalances across communities.

The idea of using maps to showcase affluence and disadvantage is not necessarily new. For example, Sampson (2012) maps concentrated disadvantage--a composite measure that looks at the proportion of welfare receipts, poverty, unemployment, female-headed households, and Black families--to understand the criminal and economic burden in areas of disadvantage (see also Dreier, Mollenkopf, & Swanstrom, 2014; Morenoff, Sampson, & Raudenbush, 2001; Sampson, Raudenbush, & Earls, 1997). Cutter, Boruff, and Shirley (2003) use a Social Vulnerability Index (SoVI)--a composite measure that looks at variables of: access to medical services, commercial and industrial development, demographics, employment, family stability, infrastructure, socioeconomic status, social dependence, and education--to map social vulnerability to environmental hazards across US counties (see also Cutter & Finch, 2008; Rygel, O'Sullivan, & Yarnal, 2006).

What Sampson (2012) and Cutter et al. (2003) do not mention is using their research as counter-maps. Counter-mapping, as Peluso (1997) notes, is about creating maps with the potential to freeze "the dynamic social processes which are referred to as 'customary law'" (p. 400). Essentially, counter-maps both acknowledge the status quo and aim to destabilize the normal order's power. In doing so, the map becomes a negotiation tool for abject peoples. For the purposes of this discussion, the key difference between GIS and critical GIS is that the former accepts the normal order as a matter-of-fact and, in doing so, becomes a hegemonic tool; the latter rejects these assumptions and highlights the transformative power of GIS to force change. Counter-maps, as a form of critical GIS, can show why Trayvon's presence was so uncanny to Zimmerman and, broadly, can unearth sites of cultural, economic, and social conflict across communities.

Mapping Affluence and Disadvantage in Sanford

Although Sampson's (2012; see also Sampson et al., 1997) concentrated disadvantage and Cutter et al. (2003) Social Vulnerability Index (SoVI) have not been used as part of a critical GIS agenda, these composite measures have the potential to showcase areas of affluence and disadvantage across Sanford. To recreate these composite measures, I accessed the Census Bureau's (2016, Sept. 16) Topologically Integrated Geographic and Referencing (TIGER) database to download the 2010 and 2015 American Community Survey (ACS) five-year block-group geodatabases for the entire State of Florida. These geodatabases include spatial extracts of Florida's block-groups, which I joined to the pertinent ACS data via ArcMAP 10.5.1. Thereafter, I used ArcMAP to create geocoded ACS files for the 44 block-groups found to be within or intersecting the Sanford city limits. Each Sanford ACS file contained over 1,800 variables covering demographic, social, economic, and housing statistics across the selected 44 block-group observations. Using StatTransfer 13.0, I exported the geocoded Sanford ACS files to Stata 15.0, which I used to trim the data down to 61 variables (Table 2) previously used by either Sampson et al. (1997) and/or Cutter et al. (2003). Of the five axes of power outlined in Table 1, the selected variables account for the intersection of race structures, gender structures, and systems of economic oppression. However, systems of sexuality and cultural oppression are not directly measured.

To create their composite measures, both Sampson et al. (1997) and Cutter et al. (2003) use factor analysis. Brown (2015) and Fabrigar, Wegener, MacCallum, and Strahan (1999) note that the goal of factor analysis is to develop a terse conceptual understanding of a set of measured variables by identifying unobservable latent variables (or factors) that impact more than one measured variable and explain the covariance among them. Thus, like Sampson et al. (1997) and Cutter et al. (2003), I conducted a principal-component factor (PCF) analysis, followed by an orthogonal varimax rotation for the 44 block-group observations across the selected 61 variables. Table 3 shows loadings for the factor with the largest eigenvalue in both ACS 2010 and ACS 2015.

Affluence and disadvantage in Sanford, 2010. Although the PCF analysis produced several factors, Factor 1 explains 23% and 20% of the variance in the data (Table 3). Moreover, Factor 1 exhibits a critical distinction between conditions of affluence and disadvantage. Accordingly, in 2010, living in a home worth less than $125,000 (.87), having an income-to-poverty ratio below 2.00 (.83), living in a female-headed household (.81), living below the poverty line (.77), being a woman without a high school diploma (.76), and being Black (.73) in Sanford are all indicators that load significantly (>.7) and positively on Factor 1 (Cronbach a = .95). In contrast, increasing the median value of homes (-.91), earning more than $75,000 (-.89), living in a home worth more than $500,000 (-.85), increasing the per capita income (-.84), being a man with a graduate degree (-.77), and being White (-.76) in Sanford all significantly (>-.7) counterbalance the positive Factor 1 loadings. As such, Factor 1 is both a measure of affluence (i.e., a negative Factor score) and disadvantage (a positive Factor score).

To map Factor 1, an option is to sum the Factor 1 variables according to their loading signs (positive or negative), which aligns with the Sampson et al. (1997) and Cutter et al. (2003) methods. Another option is to predict factors scores using a linear combination between the observed variables and the factor (DiStefano, Zhu, & Mindrila, 2009; see also Sampson, Sharkey, & Raudenbush, 2008). While both methods produce similar maps of Sanford, the latter maximizes validity and produces unbiased estimates of the true factor scores (DiStefano et al., 2009). Hence, Map 1 shows the 2010 Factor 1 linear scores across Sanford by quadrants. Block-groups with the highest positive scores (top 25%) make up quadrant 4 (Q4) and block-groups with the lowest scores (bottom 25%) make up quadrant 1 (Q1). Effectively, Q4 block-groups exhibit extreme disadvantage compared to other block-groups in Sanford, and Q1 block-groups exhibit extreme affluence compared to other block-groups in Sanford. Per Map 1, disadvantage clusters around Sanford's center (explicitly, block-groups 11, 12, 13, 16, 17, 18, 19, 33). As one moves out west or east from this cluster, conditions of affluence arise. Not only are the affluence and disadvantage differences between quadrants geographically clear, these differences are also statistically significant across a series of indicators (Table 4).

Affluence and disadvantage in Sanford, 2015. On the one hand, in 2015, living in a home worth less than $125,000 (.91) and living in a female-headed household (.76) load significantly (>.7) and positively on Factor 1 (Cronbach a = .94). Although having an income-to-poverty ratio below 2.00 (.64) and being Black (.61) are not as significant as in 2010, these variables are still strongly indicative of disadvantage in Sanford. On the other hand, increasing the median value of homes (-.88), living in a home worth more than $500,000 (-.86), earning more than $75,000 (-.85), increasing the per capita income (-.79), being married (-.75), and increasing rent prices to more than $1,250, all significantly (>.7) counterbalance positive Factor 1 loadings. Map 2 shows the 2015 Factor 1 scores by quadrants. In 2015, disadvantage continues to cluster in the middle (BGs 11, 12, 13, 16, 17, 18, 19, 33). However, compared to 2010, more eastern block-groups are in Q3 and Q4--from 5 (BG 1, 4, 6, 34, 35) to 7 (BG 4, 6, 9, 34, 35, 36, 38)--and the western block-groups remain affluent. Once again, there are statistically significant differences between block-groups across a series of indicators (Table 5).

SANFORD'S THRESHOLDS AND THE STATE OF EXCEPTION

In 2010, two years prior to Trayvon's death, the Retreat at Twin Lakes (i.e., George Zimmerman's neighborhood; BG 20) was surrounded by areas of considerable affluence. Areas where, on average: 60% of Q1 and 40% of Q2 homes were worth between $300,000 and $500,000; 19% of Q1 and 15% of Q2 men had earned undergraduate degrees; 22% of Q1 and 7% of Q2 rent agreements asked for more than $1,250 monthly; and 72% of Q1 and 62% of Q2 residents were White (Table 4). Arguably, these western block-groups (Map 1) represent areas of normal order. In 2015, three years after Trayvon's death, the Retreat at Twin Lakes was still surrounded by areas of advantage (Map 2). The extreme differences between quadrants, specially between Q1 and Q4, point to invisible thresholds that divide Sanford. Thresholds that maintain the normal order by confining individuals to specific areas in the city.

Why did Zimmerman make the choice to pursue Trayvon? Why was Trayvon's presence so alarming to Zimmerman's presumed normal order? Unbeknown to Trayvon, his presence at the Twin Lakes gated community was a challenge to George Zimmerman's normal order. It did not matter that Trayvon was not actually from Q4 or Q3, because, in Sanford, it was enough that he looked as if he belonged to these sites of disadvantage. Zimmerman could not look beyond Sanford's invisible thresholds. He could not conceive any other explanation for Trayvon's existence other than "he's up to no good." He could not see Trayvon as a fellow human-being whose actions were as reasonable as his own. Instead, Trayvon was expected to act accordingly: do not walk through a middle-class neighborhood in the rain, do not hold candy and iced tea, do not look at the oppressor, do not follow the oppressor, do not fight back.

CONCLUSION

The administrative state does not act, public servants do. And if would-be public servants like Zimmerman (a neighborhood watch coordinator) have the discretion to decide on the exception on behalf of the People, the administrative state needs to be held accountable. The normal order--Q1 and Q2 in Sanford--exists thanks to systems of oppression that guarantee the dehumanization of abject peoples. When Trayvon unknowingly crossed the threshold over to Zimmerman's neighborhood, the adolescent was first dehumanized and then killed. As Trayvon's death shows, decisions about who belongs and does not belong, made on behalf of the public, unearth important discussions about the role of the public servant vis-a-vis historically abject subjects. Without a doubt, the factors associated with the death of Trayvon Martin are more complex than the counter-maps and tables created here. There are obvious limitations to the study, starting with variables that do not account for systems of sexuality and cultural oppression, using block-groups instead of a different geographic unit of analysis, focusing on Sanford two years prior to Trayvon's death and three years after without looking at 2012, and relying on Zimmerman's 911 call to make claims about his own decision-making. Yet, as a project to excavate exclusion and oppression, this study offers different perspectives to start conversations about violence against anOther--specially Quijano's (1992; 2000) work, which introduces a postcolonial perspective from Latin America--and demonstrates how GIS can be used to challenge the normal order.

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ESTEBAN LEONARDO SANTIS

University of Central Florida
Table 1.
Archeology of Exclusion

Condition                                Decision Points and Logic

Normal Order - rule of law and           a) X believes, or needs, Y to
membership according to the People.         be less than X.
Enforced through:                        b) X creates and implements
1. Race structures that sanction white      constraints, or norms, that
   supremacy.                               force Y to perform as less
                                            than X.
2. Gender structures that view men as    c) Since Y performs as less
   rational actors and women as             than X, it is a
   insensible objects.                      matter-of-fact that Y is
                                            less than X.
3. Systems of sexuality that favor       d) X can justify oppression
   heterosexism.                            since Y is less than X.
4. Systems of economic oppression on
   behalf of a capitalist structure.
5. Systems of cultural oppression and
   erasure that uphold Western values
   and silence non-Western beliefs.
The State of Exception - a decision to   a) X believes, or needs, Y to
redefine the limits (or zones of            be less than X.
indistinction) of membership to exclude  b) X creates and implements
undesirable members/Others.                 constraints, or norms, that
Enforced when:                              force Y to perform as less
                                            than X.
1. The abject (undesirable)              c) Y does not perform as less
   challenges the normal order.             than X.
                                         d) Since Y does not perform as
                                            less than X, Y is excluded
                                            (abjected).

Table 2.
Variable Names and Descriptions (1)

AVGPERHH          Average household size of occupied housing units
HODENUT           Number of housing units per square mile
MEDAGE            Median age
MVALOO15          Median value of owner-occupied housing (in dollars)
PCTAGRIP          % employed in primary extractive industries
                  (agriculture, forestry, fishing and hunting, and
                  mining) (2)
PCTASIAN          % Asian
PCTBLACK          % African American
PCTDIVORCE        % of population 15 years or older with a divorce (2)
PCTF HH           % of female-headed households (no spouse present)
PCTGRAD           % of population with an undergraduate degree (2)
PCTHH75           % of households earning more than $75,000
PCTHHVALOVER500   % of owner-occupied housing units valued at >
                  $500,000
PCTHHVALSUB125    % of owner-occupied housing units valued at <
                  $125,000
PCTHHVALSUB200    % of owner-occupied housing units valued > $125,000
                  and < $200,000
PCTHHVALSUB500    % of owner-occupied housing units valued > $200,000
                  and < $500,000
PCTHISPANIC       % Hispanic (3)
PCTINDIAN         % Native American
PCTKIDS           % of population under age 5 (2)
PCTLBR            % of people participating in civilian labor force (2)
PCTMARRIED        % of population married
PCTMOBL           % of housing units that are mobile homes
PCTNOHS           % of population without a high school diploma (2)
PCTOLD            % of population over age 65 (2)
PCTPAIBEN         % of households receiving Public Assistance Income
                  (PAI) in the past 12 months
PCTPHD            % of population with doctoral degree (2)
PCTPOSTGRD        % of population with graduate degree (2)
PCTPOV            % living in poverty
PCTRENT OVER1250  % contract rent over $1,250
PCTRENT SUB1250   % contract rent > $600 but < $1,250
PCTRENT SUB600    % contract rent < $600
PCTRENTER         % renter-occupied housing units
PCTSERV           % employed in service occupations (healthcare
                  support, protective service, food preparation and
                  serving, building and grounds cleaning and
                  maintenance, and personal care) (2)
PCTSPRTD          % of population 15 years or older who are separated
                  from spouse (2)
PCTSSBEN          % of households receiving Social Security in the past
                  12 months
PCTSSIBEN         % of households receiving Supplemental Security
                  Income (SSI) in the past 12 months
PCTSTRUNITSOVER5  % of dwellings with 5 or more housing units
                  (structural density)
PCTSUB2INCPVRTY   % of population with an income-to-poverty ratio below
                  2.00
PCTTRAN           % employed in production, transportation, and
                  material moving occupations (2)
PCTVACUNITS       % of vacant housing units
PCTVEHICLE 0      % of households without access to a vehicle
PCTVEHICLE OVER3  % of households with access > 3 vehicles
PCTVEHICLE SUB3   % of households with access > 0 but < 3 vehicles
PCTWHITE          % White
PCTWIDOW          % of population 15 years or older who are widows (2)
PCTYOUNG          % of population under age 18 but > 5 (2)
PERCAP            per capita income (in dollars)

(1.) Variable names mimic Cutter et al. (2003)
(2.) Indicates the variable was measured for both females (F) and males
(M)
(3.) Indicates the variable was measured for both Hispanic/Black and
Hispanic/White

Table 3.
Factor 1 Loading (Affluence and Disadvantage)

ACS 2010 (Sanford, FL)                    ACS 2015 (Sanford, FL)
Variable           Factor 1        Variable           Factor 1
(across 44 obs.)   [alpha] = .95   (across 44 obs.)   [alpha] = .94

PCTHHVALSUB125              0.87   PCTHHVALSUB125              0.91
PCTSUB2INCPVRTY             0.83   PCTF HH                     0.76
PCTF HH                     0.81   PCTSUB2INCPVRTY             0.64
PCTPOV                      0.77   PCTBLACK                    0.61
PCTNOHS F                   0.76   PCTNOHS M                   0.54
PCTBLACK                    0.73   PCTSPRTD F                  0.54
PCTRENTER                   0.54   PCTVACUNITS                 0.54
PCTNOHS M                   0.51   PCTTRAN M                   0.44
PCTTRAN M                   0.51   PCTVEHICLE OVER3           -0.52
PCTPAIBEN                   0.46   PCTASIAN                   -0.56
HODENUT                     0.43   PCTHHVAL SUB200            -0.63
PCTRENT OVER1250           -0.51   PCTPOSTGRD M               -0.64
PCTPOSTGRD F               -0.53   PCTGRD M                   -0.65
PCTGRD F                   -0.56   PCTWHITE                   -0.69
PCTVEHICLE OVER3           -0.59   PCTRENT OVER1250           -0.72
PCTHHVAL OVER500           -0.61   PCTMARRIED                 -0.75
PCTPOSTGRD M               -0.65   PERCAP                     -0.79
PCTMARRIED                 -0.67   PCTHH75                    -0.85
PCTWHITE                   -0.76   PCTHHVAL SUB500            -0.86
PCTGRD M                   -0.77   MVALOO                     -0.88
PERCAP                     -0.84
PCTHHVAL SUB500            -0.85
PCTHH75                    -0.89
MVALOO                     -0.91
[[sigma].sup.2] (% of      14.2    [[sigma].sup.2] (% of      12.2
[[sigma].sup.2]            (23%)   [[sigma].sup.2]            (20%)
explained)                         explained)

Table 4.
2010 ACS (Sanford, FL): Mean Differences between Quadrants (1)

Variable             Q1                      Q2
                     mean (sd; min: max)     mean (sd; min: max)


MVALOO (2)           $281,618                $193,882
                     ($73,083;               ($24,826;
                     $163,800:               $149,300:
                     $369,300)               $228,600)
PCTBLACK (2)           11% (9%; 1%: 28%)       12% (17%; 0%: 59%)
PCTFHH (2)              8% (4%; 0%: 15%)       19% (8%; 4%: 29%)
PCTGRDM (2)            19% (4%; 13%: 28%)      15% (6%; 3%: 29%)
PCTHH75 (2)            47% (16%; 20%: 80%)     32% (6%; 20%: 39%)
PCTHHVAL_OVER500       12% (10%; 0%: 31%)       2% (2%; 0%: 5%)
PCTHHVAL_SUB125 (2)    11% (10%; 0%: 32%)      19% (8%; 7%: 33%)
PCTHHVAL_SUB200 (2)    18% (13%; 2%: 43%)      39% (12%; 24%: 61%)
PCTHHVAL_SUB500 (2)    60% (17%; 32%: 82%)     40% (16%; 12%: 63%)
PCTMARRIED (2)         56% (9%; 36%: 66%)      48% (9%; 33%: 63%)
PCTNOHS_F (2)           4% (3%; 0%: 11%)        5% (3%; 1%: 10%)
PCTNOHS_M (2)           6% (6%; 0%: 18%)        5% (2%; 2%: 9%)
PCTPOSTGRD_F            5% (3%; 2%: 11%)        4% (3%; 0%: 9%)
PCTPOSTGRD_M (2)        8% (5%; 0%: 19%)        4% (3%; 1%: 9%)
PCTPOV (2)              6% (4%; 1%: 12%)        8% (4%; 2%: 12%)
PCTRENT_OVER1250 (2)   22% (23%; 0%: 72%)       7% (9%; 0%: 22%)
PCTRENTER              16% (12%; 0%: 41%)      19% (10%; 6%: 42%)
PCTSERVM                5% (4%; 0%: 11%)        7% (7%; 0%: 24%)
PCTSPRTD_F (2)          2% (3%; 0%: 9%)         7% (6%; 0%: 17%)
PCTSUB2INCPVRTY (2)    16% (7%; 6%:  28%)      19% (5%; 10%: 28%)
PCTVEHICLE0             4% (5%; 0%: 14%)        3% (3%; 0%: 9%)
PCTVEHICLE_OVER3 (2)   21% (10%; 4%: 44%)      18% (7%; 6%: 33%)
PCTWHITE (2)           72% (14%; 42%: 88%)     62% (18%; 23%: 86%)
PERCAP (2)            $34,387                 $26,541
                      ($8,951; $24,217:       ($4,753; $19,141:
                      $52,024)                $34,528)

Variable             QQ3                     Q4
                     mmean (sd; min:         mean (sd; min:
                      max)                   max)

MVALOO (2)           $$143,664                $92,545
                     ($44,792;               ($31,849;
                     $ $65,000:               $33,900:
                     $$205,000)              $129,900)
PCTBLACK (2)            27% (20%; 5%:69%)      65% (28%; 18%: 100%)
PCTFHH (2)              31% (13%; 13%: 59%)    52% (21%; 21%: 100%)
PCTGRDM (2)              9% (5%; 2%: 17%)       3% (4%; 0%: 13%)
PCTHH75 (2)             18% (9%; 4%: 34%)       6% (8%; 0%: 21%)
PCTHHVAL_OVER500         1% (2%; 0%: 6%)        0% (1%; 0%: 3%)
PCTHHVAL_SUB125 (2)     38% (22%; 10%: 78%)    71% (19%; 44%: 100%)
PCTHHVAL_SUB200 (2)     39% (13%;14%: 61%)     25% (16%; 0%:48%)
PCTHHVAL_SUB500 (2)     22% (15%; 0%: 49%)      4% (5%; 0%: 15%)
PCTMARRIED (2)          43% (15%; 20%: 70%)    31% (12%; 13%: 56%)
PCTNOHS_F (2)            9% (4%; 5%: 19%)      18% (8%; 10%: 33%)
PCTNOHS_M (2)            8% (4%; 4%: 14%)      15% (11%; 2%: 39%)
PCTPOSTGRD_F             3% (3%; 0%: 12%)       1% (2%; 0%: 6%)
PCTPOSTGRD_M (2)         2% (2%; 0%: 5%)        1% (2%; 0%: 8%)
PCTPOV (2)              18% (10%; 8%: 44%)     35% (16%; 15%: 70%)
PCTRENT_OVER1250 (2)     2% (5%; 0%: 16%)       3% (5%; 0%: 14%)
PCTRENTER               38% (20%; 18%: 82%)    39%  (20%; 14%: 78%)
PCTSERVM                 9% (8%; 0%: 23%)      17% (10%; 3%: 33%)
PCTSPRTD_F (2)           6% (13%; 0%: 43%)     25% (26%; 0%: 86%)
PCTSUB2INCPVRTY (2)     38% (16%; 15%: 64%)    57% (18%; 36%: 92%)
PCTVEHICLE0             7% (13%; 0%: 42%)      21% (19%; 2%: 57%)
PCTVEHICLE_OVER3 (2)   13% (9%; 4%: 28%)        8% (7%; 0%: 20%)
PCTWHITE (2)           48% (20%; 22%: 89%)     23% (17%; 0%: 41%)
PERCAP (2)             $18,843                $12,846
                       ($2,329; $15,835:      ($3,170; $6,588:
                       $24,223)               $17,601)

(1.) Variable means across quartiles (Q1-Q4) are statistically
significantly different per one-way ANOVA results, p<.01
(2.) Variable means are statistically significantly different (p<.01)
across quartiles (Q1-Q4) in 2010 and 2015

Table 5.
2015 ACS (Sanford, FL): Mean Differences between Quadrants (1)

Variable              Q1
                      mean (sd; min: max)

HODENUT                      0.18 (0.11; 0.01: 0.35)
MVALOO (2)            $193,473 ($62,563; $108,900: $302,600)
PCTASIAN                     6% (6%; 0%: 16%)
PCTBLACK (2)                13% (10%; 0%: 32%)
PCTF HH (2)                 14% (5%; 8%: 20%)
PCTGRD_M (2)                19% (4%; 12%: 25%)
PCTHH75 (2)                 46% (11%; 24%: 64%)
PCTHHVAL_SUB125 (2)         24% (21%; 0%: 57%)
PCTHHVAL_SUB200 (2)         31% (10%; 18%: 47%)
PCTHHVAL_SUB500 (2)         41% (18%; 18%: 70%)
PCTMARRIED (2)              53% (8%; 33%: 62%)
PCTNOHS_F (2)                3% (3%; 0%: 8%)
PCTNOHS M (2)                4% (4%; 0%: 12%)
PCTPOSTGRD_M (2)             5% (3%; 1%: 11%)
PCTPOV (2)                  10% (7%; 0%: 20%)
PCTRENT OVER1250 (2)        39% (24%; 0%: 77%)
PCTSPRTD F (2)               2% (2%; 0%: 7%)
PCTSUB2INCPVRTY (2)         18% (11%; 2%: 36%)
PCTVACUNITS                 18% (9%; 7%: 37%)
PCTVEHICLEOVER3 (2)         24% (9%; 12%: 37%)
PCTWHITE (2)                65% (11%; 46%: 82%)
PERCAP (2)             $32,360
                       ($8,360; $18,468: $44,647)

Variable              Q2
                      mean (sd; min: max)

HODENUT                      0.37 (0.18; 0.05: 0.61)
MVALOO (2)            $108,182 ($26,619; $65,000: $151,600)
PCTASIAN                     3% (4%; 0%: 11%)
PCTBLACK (2)                26% (17%; 10%: 59%)
PCTF HH (2)                 24% (8%; 6%: 36%)
PCTGRD_M (2)                14% (6%; 2%: 21%)
PCTHH75 (2)                 22% (10%; 1%: 41%)
PCTHHVAL_SUB125 (2)         60% (16%; 41%: 91%)
PCTHHVAL_SUB200 (2)         28% (12%; 9%: 45%)
PCTHHVAL_SUB500 (2)          9%  (6%; 0%: 21%)
PCTMARRIED (2)              44% (7%; 33%: 57%)
PCTNOHS_F (2)                3% (3%; 0%: 9%)
PCTNOHS M (2)                4% (2%; 1%: 7%)
PCTPOSTGRD_M (2)             3% (2%; 0%: 9%)
PCTPOV (2)                  21% (11%; 5%: 45%)
PCTRENT OVER1250 (2)         5% (7%; 0%: 20%)
PCTSPRTD F (2)              10% (8%; 0%: 22%)
PCTSUB2INCPVRTY (2)         39% (15%; 10%: 64%)
PCTVACUNITS                 19% (11%; 2%: 42%)
PCTVEHICLEOVER3 (2)          9% (5%; 0%: 19%)
PCTWHITE (2)                55% (16%; 27%: 81%)
PERCAP (2)             $20,550
                       ($4,547; $13,666: $28,942)

Variable              Q3
                      mean (sd; min: max)

HODENUT                     0.40 (0.14; 0.24: 0.59)
MVALOO (2)            $90,527 ($22,026; $58,900: $140,700)
PCTASIAN                    2% (3%; 0%: 9%)
PCTBLACK (2)               28% (21%; 7%: 73%)
PCTF HH (2)                35% (17%; 20%: 68%)
PCTGRD_M (2)               11% (6%; 0%: 24%)
PCTHH75 (2)                19% (11%; 4%: 38%)
PCTHHVAL_SUB125 (2)         81% (12%; 63%: 98%)
PCTHHVAL_SUB200 (2)        14% (10%; 0%: 37%)
PCTHHVAL_SUB500 (2)         3% (5%; 0%: 18%)
PCTMARRIED (2)             37% (8%; 23%: 47%)
PCTNOHS_F (2)               8% (10%; 0%: 28%)
PCTNOHS M (2)               7% (5%; 1%: 16%)
PCTPOSTGRD_M (2)            2% (2%; 0%: 6%)
PCTPOV (2)                 20% (10%; 1%: 38%)
PCTRENT OVER1250 (2)        3% (7%; 0%: 23%)
PCTSPRTD F (2)             18% (19%; 0%: 59%)
PCTSUB2INCPVRTY (2)        40% (12%; 24%: 60%)
PCTVACUNITS                28% (14%; 0%: 41%)
PCTVEHICLEOVER3 (2)        14% (9%; 2%: 31%)
PCTWHITE (2)               46% (17%; 16%: 70%)
PERCAP (2)             $17,785
                       ($4,006; $10,824: $22,789)

Variable              Q4
                      mean (sd;  min: max)

HODENUT                     0.35 (0.12; 0.16: 0.50)
MVALOO (2)            $64,845 ($24,076; $23,900: $96,000)
PCTASIAN                    0% (1%; 0%:2%)
PCTBLACK (2)               55% (31%;16%: 100%)
PCTF HH (2)                48% (11%; 34%: 64%)
PCTGRD_M (2)                6% (4%; 0%: 12%)
PCTHH75 (2)                 9% (6%; 0%: 20%)
PCTHHVAL_SUB125 (2)        90% (10%; 74%: 100%)
PCTHHVAL_SUB200 (2)         8% (8%; 0%: 26%)
PCTHHVAL_SUB500 (2)         2%  (3%; 0%: 8%)
PCTMARRIED (2)             32% (9%; 17%: 52%)
PCTNOHS_F (2)              13% (7%; 5%: 31%)
PCTNOHS M (2)              10% (6%; 1%: 22%)
PCTPOSTGRD_M (2)            1% (1%; 0%: 3%)
PCTPOV (2)                 32% (20%; 3%: 65%)
PCTRENT OVER1250 (2)        1% (3%; 0%: 8%)
PCTSPRTD F (2)             23% (19%; 0%: 61%)
PCTSUB2INCPVRTY (2)        56% (16%; 34%: 80%)
PCTVACUNITS                34% (13%; 20%: 59%)
PCTVEHICLEOVER3 (2)        11% (6%; 2%: 18%)
PCTWHITE (2)               27% (17%; 0%: 45%)
PERCAP (2)            $13,317
                      ($3,394; $7,137: $18,123)

(1.) Variable means across quartiles (Q1-Q4) are statistically
significantly different per one-way ANOVA results, p<.01
(2.) Variable means are statistically significantly different (p<.01)
across quartiles (Q1-Q4) in 2010 and 2015
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Title Annotation:geographic information systems
Author:Santis, Esteban Leonardo
Publication:Public Administration Quarterly
Article Type:Report
Geographic Code:1USA
Date:Jun 22, 2018
Words:9576
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