Organized Crime and Human Trafficking in the United States

Organized Crime and Human Trafficking in the United States | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Organized Crime and Human Trafficking in the United States Vanessa Bouche, Sarah Van Dyk This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6597507/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Despite prevailing narratives that human trafficking is largely driven by transnational organized crime groups, little empirical research has rigorously tested this assumption. This study presents a novel 5-S typology—size, scope, sophistication, structure, and self-identification—which yields five different types of organized crime groups: mom & pop, crime rings, street gangs, illicit businesses, and cartels/mafias/syndicates. Analyzing over 2,390 federally prosecuted human trafficking cases in the United States from 2000 to 2022, we systematically assess the nexus of organized crime and human trafficking. Findings reveal that the majority of cases (67%) involve unorganized individuals, and among those involving organized crime, most are small-scale "mom & pop" operations or decentralized crime rings rather than sophisticated cartels or syndicates. While this may be a function of potential selection bias inherent in using prosecuted cases as the basis for empirical analysis, the results challenge dominant framings of human trafficking and suggest the need to recalibrate enforcement strategies and policy assumptions. The study concludes by discussing critical implications for research, practice, and the future study of organized crime and human trafficking. Human trafficking typology sex trafficking labor trafficking organized crime Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction In 2000, the United Nations set forth the “Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children”. There are several aspects of this protocol that framed the issue of human trafficking for the international community. Perhaps most notably, the Protocol took a distinctively crime-centered approach, and more specifically couched human trafficking in terms of transnational organized crime. 1 The Protocol was signed as part of the UN Convention on Transnational Organized Crime in Palermo, Sicily, “the epicenter of the old Italian Mafia, the most fabled and notorious criminal syndicate in the world” (DeStefano 2008: 28). This seminal international document, which defines human trafficking for the first time in an international context, places the issue squarely in the context of organized crime. During the drafting of the Protocol, and in the immediate years thereafter, government bodies, international organizations, and scholars all espoused the idea that transnational organized crime was behind global trafficking in persons (e.g., Bruinsma and Meershoek 1999 ; Richard 1999 ; Bruggeman 2002 ; Williams 2002 ). A body of scholarship then developed around this framing. Some of this literature examines the role of organized crime in human trafficking in specific regions of the globe, including Western Europe (Picarelli 2009 ), Russia (Finckenauer 2001 ), Canada (Bruckert and Parent 2002 ; Bruckert and Parent 2004 ), the United States (Picarelli 2009 ; Richard 1999 ), and Australia and Asia Pacific (Schloenhardt 2001 ). Other scholarship points to the role of organized crime in human trafficking as it intersects with other global issues such as migration (Väyrynen 2005 ), human smuggling (Aronowitz & Veldhuizen, 2022, p. 235) and globalization (e.g., Shelley 2010 : 40–49). While this literature collectively articulates the complexity of transnational human trafficking in the twenty-first century, there are a few limitations. First, much of this research is devoid of a clear definition of organized crime, which is problematic on a few levels. Stating that human trafficking is an issue of organized crime, without clearly defining organized crime, is tautological. It is first necessary to define organized crime, then determine the ways in which groups engaged in the crime of human trafficking meet or do not meet with various features of that definition. A definition is also necessary because it “goes a long way toward determining how laws are framed, how investigations and prosecutions are conducted, how research studies are done, and, increasingly, how mutual legal assistance across national borders is or is not rendered” (Finckenauer 2005 : 68). In other words, defining organized crime in the study of human trafficking is necessary for both philosophical and practical reasons. The second limitation is a function of the first. The extant literature framing human trafficking as an organized crime issue lacks empirical rigor. This is not necessarily unique to this body of work. Indeed, many scholars have pointed out the need for more empirical rigor in human trafficking research in general (e.g., Weitzer 2011 , 2014 ; Zhang 2012 ), and a review of 218 journal articles on human trafficking found that only 39 were based on empirical research while the remaining were non-empirical (Gozdiak 2011 ). While progress has been made in recent years (Zhang 2022 ), this lack of analytical rigor has also been used as a criticism against the claim that human trafficking is an organized crime issue: “This transnational organized crime framework has prevailed despite a lack of clear evidence of its applicability to the trafficking context or systematic analysis of criminal justice data on the profile of trafficking offenders” (Lee 2011 : 84). In other words, much of the literature citing organized crime in human trafficking does so as a matter of fact when, in the absence of solid empirical testing, it is merely an untested assumption. These theoretical and empirical weaknesses ultimately serve to legitimize criticism regarding anti-trafficking policies and practices (e.g., Woodiwiss and Hobbs 2008). The purpose of the present paper is to begin correcting for some of these gaps. First, we define organized crime by setting forth the “5-S” framework, which categorizes different types of organized crime groups along five dimensions: size, scope, structure, self-identification, and sophistication. The way groups vary along these combinations of dimensions determines the type: mom & pop, crime ring, street gang, cartel/mafia/syndicate, or illegal enterprise. Next, we examine over 2,390 different human trafficking cases prosecuted in the United States to determine the extent, manner, and type of organized criminal engagement in human trafficking in the United States. We find that the vast majority of federal human trafficking prosecutions do not involve any elements of what can be considered organized criminal activity. Further, the majority of prosecutions that can be characterized as organized crime appear to be much smaller operations than previously believed, with most being mom & pop. That does not mean they are not organized; indeed, these mom & pop groups can be highly sophisticated with an international scope of operations, but they are smaller networks that do not represent the stereotypical understanding of organized crime. Additionally, the results suggest that, while most groups can be characterized as mom & pop, there is significant variance in terms of scope and sophistication among groups engaged in different types of human trafficking. For instance, labor and adult sex trafficking organizations tend to be more sophisticated with a broader scope of operations than groups engaged in minor sex trafficking. While this paper takes the first step to clearly set forth a definitional typology and then empirically decipher organized crime groups engaged in human trafficking, the conclusions must be placed in the appropriate context. At best, the results reflect what can be discerned about these groups based on information in cases that have been federally prosecuted. Of course, there is a universe of actors that have evaded federal law enforcement detection or for whom evidence is not strong enough to indict. It is not unreasonable to hypothesize that those who have gone completely undetected are organized crime groups with strict discipline and nodal structures that are larger and more complex networks than a mom & pop structure. In other words, conclusions reached based on data available through federal prosecutions may be unique to the types of groups that get prosecuted, and not necessarily to the larger universe of actors engaged in human trafficking. Organized Crime & Human Trafficking Organized crime is an elusive concept, so difficult to define that The Organized Crime Control Act of 1970 (P.L. 91–452, 84 Stat. 922) itself did not define it. The United Nations Convention Against Transnational Organised Crime (2000) defined “an organised criminal group” in Article 2(a) as “a structured group of three or more persons, existing for a period of time and acting in concert with the aim of committing one or more serious crimes or offences established in accordance with the Convention, in order to obtain, directly or indirectly, a financial or other material benefit.” While this definition is useful for the purpose of informing international law, it is “a very broad, sort of least common denominator definition” (Finckenauer 2005 : 68). 2 Finckenauer ( 2005 : 65) combines dimensions of organized crime proposed by Hagan ( 1983 ) and Maltz ( 1985 , 1994 ) and derives eight “dimensions and characteristics” of organized crime groups. These eight dimensions are: ideology, structure/organized hierarchy, continuity, violence/use of force or the threat of force, restricted membership/bonding, illegal enterprises, penetration of legitimate businesses, and corruption. Abadinsky ( 2010 : 3) also sets forth eight attributes of organized crime groups: no political goals, hierarchical, limited or exclusive membership, unique subculture, perpetuates itself, willingness to use illegal violence, monopolistic, and explicit rules and regulations. These characteristics intersect with the Finckenauer ( 2005 ) attributes to produce a relatively comprehensive descriptive understanding of the factors that separate organized crime groups from other types of criminals. The Omnibus Crime Control and Safe Streets Act of 1968 (Pub. L. No. 90–351, 82 Stat. 197) defined organized crime in large part based on the types of crimes in which these groups engage. It states: Organized crime means the unlawful activities of the members of a highly organized, disciplined association engaged in supplying illegal goods and services, including but not limited to gambling, prostitution, loan sharking, narcotics, labor racketeering, and other unlawful activities of members of organizations. Human trafficking fits nicely into this list of the types of activities in which organized crime groups engage, especially as it intersects with prostitution and labor racketeering. Thus, between the descriptions of the group-based characteristics of criminal organizations, and the crime-types described as those in which criminal organizations engage, it is not surprising that those writing about human trafficking in the early years after the passage of the Palermo Protocol couched human trafficking in terms of organized crime. Using this problem frame, scholars began to decipher between different types of organized crime groups engaging in human trafficking, but with an understanding that defining human trafficking as an “organized crime” can mean different things. “Traffickers may be individual entrepreneurs, small ‘mom and pop’ operations, or sophisticated, organized rings. There is little consensus among those who have studied the problem as to the proportions of each of those types; nor with respect to their level of organization and sophistication” (Finckenauer and Schrock 2001: 2). Shelley ( 2003 ) set forth a typology that includes different models for groups engaging in trafficking in persons: the natural resource model, trade and development, supermarket, violent entrepreneurs, and traditional slavery/modern technology. Williams ( 2008 ) offered a typology of human trafficking groups that is slightly different. Rather than focusing on the different types of business models for engaging in human trafficking, he focuses on the different types of groups, which include opportunistic amateurs, transnational criminal organizations with broad portfolios of activity, traditional criminal organizations, ethnically-based trafficking organizations, and criminal controlled businesses. 3 A third typology was offered by Picarelli ( 2009 ). He argues there are three broadly defined types of groups engaging in human trafficking: The first are small trafficking groups comprised mainly of a handful of entrepreneurial individuals. Second are cooperatives comprised of individuals, small groups and even criminal organisations that combine specialised skills to form larger trafficking syndicates. Last are situations where one large criminal organisation controls all aspects of a trafficking network. (p. 116) Finally, Albanese ( 2011 : 54) frames a typology around what he calls a “criminal enterprise approach”. His typology includes recruiters, transporters, and exploiters who may be organized differently and who all have different goals (pp. 55–56). All of these typologies of human trafficking organizations are helpful in that they begin to fill the vacuum of definitional clarity and paint a picture of the diversity of groups engaged in human trafficking. Where they are lacking, however, is in parsimony. Building on these extant typological frameworks, I propose the “5-S” typology of organized human trafficking groups operating in the United States. 5-S Typology of Organized Crime The 5-S typology of organized human trafficking groups is named for five attributes (all starting with the letter “s”) of organized crime groups: size, scope, sophistication, structure, and self-identification. Each of these attributes has been discussed in one form or another as key characteristics of organized crime groups. For example, Finckenauer ( 2005 : 75) directly addresses issues of sophistication, structure, and self-identification, and many scholars have addressed the variance in group size and scope of operation. Thus, each attribute of the 5-S typology is not new; rather, it is organized in a way that is parsimonious, easily digestible, and useful for empirical analysis. The first “s” is size. This, of course, refers to the number of people that are “members” of the organized crime group. Implicit in the UN definition of organized crime is that size can vary dramatically. It states that an organized criminal group may be comprised of “three or more persons”. In the United States, 18 U.S.C. 371 defines conspiracy—a charge commonly used in cases involving organized crime—as an agreement between “two or more persons” to commit a criminal act. Both the UN definition of an organized criminal group and the U.S. federal definition of conspiracy indicate that organized crime groups can range from very small to very large. Thus, size is an ordinal variable that ranges from small, medium, large. Second is scope, which refers to the territorial range of the group’s operation. Organized crime groups operating in the United States may operate only in a specific locality (city or state), across state lines, or transnationally. It is important to note that much of the literature on organized crime groups has had a distinctive transnational focus. This may be the result of globalization and the factors that have made it easier to move goods and people illicitly around the globe. Indeed, “organized crime group” was defined in the UN Convention on Transnational Organized Crime. However, to be considered an organized crime group, operating transnationally is neither a necessary nor a sufficient condition. Therefore, scope is a nominal variable that is coded: local, national, transnational. Sophistication is the third “s” in the 5-S typology. In describing sophistication, Finckenauer ( 2005 : 75) asks these questions: “What degree of planning is used in carrying out crimes? How long do individual criminal ventures last? How much skill and knowledge are required in carrying out these crimes?” I define sophistication as the complexity of the group’s organized criminal activities and the extent to which their portfolios are diversified. Shelley’s ( 2003 ) “violent entrepreneurs” and “traditional slavery/modern technology” types would be considered more sophisticated under this definition as their criminal portfolio is heterogeneous, either as a means of carrying out their human trafficking activities (e.g., visa fraud, money laundering, etc.), or because they are engaged in crimes beyond trafficking in persons (e.g., drug trafficking or terrorism). On the other hand, Williams ( 2008 ) “opportunistic amateurs” would be low in sophistication as their criminal portfolios are relatively homogeneous and the operating procedures are relatively simple. Sophistication is therefore an ordinal variable coded low, medium, high. The fourth “s” is structure, which refers to the extent to which the group is structured hierarchically or is decentralized. Many definitions of organized crime groups refer in some way to the organizational structure of the group, and specifically to the hierarchical nature of the groups (e.g., Abadinsky 2010 ; Hagan 1983 ; Maltz 1985 , 1994 ; Finckenauer 2005 ). For example, Abadinsky ( 2010 : 3) states, “An organized crime group has a vertical power structure with at least three permanent ranks—not just a leader and followers—each with authority over the level beneath.” However, other definitions do not view hierarchy as a necessary condition to defining an organized criminal group. In defining organized crime groups as being comprised of “a structured group of three or more persons,” the UN Convention on Transnational Organized Crime makes provision for all sorts of organizational structures beyond those that are hierarchical. Therefore, I argue that organized crime groups may vary in their structure, and I use an ordinal coding structure that includes: very decentralized, somewhat decentralized, somewhat hierarchical, very hierarchical. Finally, the last “s” in the 5-S typology of organized crime groups refers to self-identification. Self-identification has two sub-categories: 1) name; and 2) type of identification. Name simply refers to whether or not a group has a proper name. This can be a gang name, such as Bloods, or a business name. Therefore, name is coded simply as yes or no. Type of self-identification refers to the identity around which the group is formed. For example, ethnicity has been a major identity around which government agencies and scholars have understood organized crime groups; however, ethnicity is not the only identity around which organized crime groups form. Albanese ( 2011 : 5) refers to this as the “ethnicity trap” and argues that “the use of ethnicity as a descriptor of criminal activity is extremely limited.” Another type of self-identification can be region, biological family, prison groups, or motorcycle gangs. The key here is not the specific type of self-identification, but whether or not the group is organized around a common identifying characteristic beyond banding together to commit a criminal act. Thus, type of self-identification is a nominal variable with the following categories: family, friend, family/friend, race/ethnicity, accomplices, gang members. [INSERT TABLE 1 ABOUT HERE] Variance across the 5-S typology generates five different types of organized crime groups. The first type is “Mom & Pop.” This type of group is defined by size and self-identification. The size of a mom & pop group is small. Although it is difficult to put a firm number to the size, as a general matter, a mom & pop group would constitute less than 10 people. In addition to size, mom & pop groups are also defined by self-identification wherein the type of self-identification is family or friends with no proper name for the group. Mom & pop groups cannot be defined by sophistication, scope, or structure because they can vary dramatically in all three of these categories. The second type of group generated by the 5-S typology is “Crime Ring.” A crime ring is defined by its structure in that it must be extremely or somewhat decentralized with no boss or rigid hierarchy. Crime rings can also be differentiated from other groups in that the strength of self-identification as a group is weak, they are not organized around any particular type of identity such as race, ethnicity, or family, but rather as accomplices, and there is no proper name with which the group associates itself. Crime rings cannot be differentiated from other types of organized crime groups based on sophistication, scope, or size because crime rings can vary along these dimensions. “Street Gang” is the third type of group generated by the 5-S typology, and street gangs are defined based on their scope and self-identification. In order to be classified as a street gang, the group must operate either locally or nationally. If a group operates transnationally, then it is not classified as a street gang. They are also distinct in their self-identification. The strength of their self-identification is strong, the type of self-identification is well-defined, and the name of the group is proper and distinct. Street gangs cannot be classified as such based on size, sophistication, or structure because all of these can be variable for these types of groups. The fourth classification is “Cartel/Mafia/Syndicate.” I use these three words interchangeably because they can all be classified based on the same set of criteria. First, these groups must be large, with hundreds or even thousands of members. Second, cartels/mafias/syndicates must have a transnational scope of operations. If they operate only in one location or one state, then they are not a cartel/mafia/syndicate. Third, these types of groups are highly sophisticated and have a heterogeneous portfolio of criminal activities. In terms of structure, these groups must be hierarchical with clear bosses or kingpins. Thus, cartels/mafias/syndicates may be defined as such based on size, scope, sophistication, and structure. Their self-identification, on the other hand, varies across strength, type, and name and cannot necessarily be used as a condition for classification. The final type is “Illegal Enterprise.” The defining characteristics of illegal enterprises are sophistication and self-identification. Illegal enterprises are highly sophisticated in that they engage in a variety of complex criminal activities. In setting up the illegal enterprise, these groups must often engage in a variety of conspiratorial acts against the government, including money laundering, tax evasion, document fraud, and extortion. Additionally, illegal enterprises can be classified as such based on self-identification wherein the type of identification is a business. Moreover, the name of the business is an official and proper name. Illegal enterprises vary on all other classification dimensions, including size, scope, and structure. Overall, the 5-S typology is a parsimonious framework to understand the diversity of actors engaged in human trafficking in the United States and the dimensions on which they vary. The next two sections explain the methodology for collecting cases and provide the results of the analysis. Methodology In order to examine the extent to which organized crime (as defined by the 5-S typology) is engaged in human trafficking in the United States, we examined all of the federally-prosecuted human trafficking cases across the United States from 2000 to 2022. Allies Against Slavery collects the cases by searching Bloomberg Law using a very specific keyword search protocol, which includes search terms relevant to different types of human trafficking, as well as search terms relevant to organized criminal cases, such as RICO, conspiracy, gang, organized crime, racketeering, mafia, cartel, or document fraud. After conducting the searches, the research team sorts the cases to discard false positives and ensure that the facts of the case clearly indicate human trafficking. 4 Finally, the research team downloads case documents–docket reports, indictments, criminal complaints, and/or sentencing memoranda–in order to stage the case in preparation for coding. The research team also conducts media searches using Access World News and Google News for each of the cases. Some cases have an abundance of news coverage, while others have none. After collecting the cases, the research team begins the process of coding the cases in accordance with a very exhaustive and detailed case coding protocol. 5 Using the information contained in the case documents and news articles, key variables are extracted at the case level and the defendant level. At the case level, the research team codes for things like the state, federal district, and year of the prosecution, the type of human trafficking involved, the criminal methods used by the traffickers, crime locations and routes, and victim information including number of victims and their demographic characteristics (age, nationality, gender). At the defendant level, the research team extracts demographic information about the defendant (age at arrest, race/ethnicity, gender), and all charging and sentencing details. In addition, the team codes for organized crime using the 5-S typology in order to determine if the person or people involved in the case is/are acting in an unorganized manner, or can be classified as mom and pop, crime ring, street gang, cartel/mafia/syndicate, or illegal enterprise. The data was then analysed using RStudio (RStudio Team, 2023) and the packages tidyverse, lmtest, sandwich, stargazer, reshape2, ggridges, foreign, nnet, and forcats (Wickham et al 2009, Zeileis and Hothorn 2002 , Zeileis et al 2020 , Hlavac 2022 , Wickham 2007 , Wilke 2024 , R Core Team, 2025 , Venables and Ripley 2002 , Wickham 2023 ). First, summary statistics were calculated. Then we fit multiple bivariate multinomial logit regression models comparing labor and minor sex trafficking to adult sex trafficking, as well as adult sex trafficking and labor trafficking to minor sex trafficking to allow for comparison of each form of trafficking to each other form of trafficking. 6 Only cases with complete data across all independent and dependent variables were included (n = 510). Given that repeated bivariate tests are associated with Type I error, we then adjusted p-values using the Bonferroni adjustment (Cabin and Randall 2000). Finally, we repeated the same process of fitting bivariate multinomial regression models using Bonferroni adjustments to compare the predicted probability of engagement in trafficking crime type based on crime group type. These were conducted where the independent variable was a binary variable of either being the group of interest (i.e. Mom & Pop) or all other groups. The dataset includes 2,390 federally prosecuted human trafficking cases from 2000 to 2022 involving a total of 4,557 defendants and 11,495 identified victims. Below, we present the results of the 5-S typology of organized crime and human trafficking in the United States as evidenced in federal human trafficking prosecutions. Results Figure 1 details the distribution of organized crime classifications for all cases in the dataset. The first major finding is that, among federally prosecuted human trafficking cases, the majority (67%, n = 1,592) are unorganized. 7 The differences in means between the total number of organized versus unorganized cases is statistically significant (p < 0.001). In other words, federal investigators and prosecutors are spending a disproportionate amount of time and resources on cases that do not indicate any type of organized criminal activity per the 5-S typology. [INSERT FIGURE ABOUT HERE] There are a total of 635 cases that can be classified as involving organized crime, which had a total of 2,381 defendants. Among those, a combined 69% are Crime Rings (48%; n = 306) and Mom & Pop (21%; n = 134). As we investigate the 5-S typology more deeply, it becomes clear that, while the majority of federal human trafficking prosecutions do not indicate any level of organized criminal activity at all, those that do mostly represent relatively small and unsophisticated types of organized crime groups. [INSERT FIGURE 2 ABOUT HERE] The first S is size of the organization. It is important to note that the number of defendants in the case does not necessarily indicate the total size of the group. For example, a Cartel/Mafia/Syndicate is extremely large, often with hundreds or thousands of members; however, it is possible that only one member of the Cartel/Mafia/Syndicate is a defendant in a case with no co-defendants. That said, the number of co-defendants generally does reflect the size of the group. Crime Rings have the lowest number of defendants per case at 3.0 (st. dev. 3.1) and Mom & Pop groups have the next lowest with 3.5 (st. dev. 3.0) defendants on average per case. These are also the two smallest types of organized crime groups, and the difference in means between them is not statistically significant. This is significantly different than the other organized crime group types. Illegal Enterprises have an average of 4.8 (st. dev. 4.8) defendants per case, Street Gangs have 5.4 (st. dev. 7.5), and Cartels/Mafias/Syndicates have 6.3 (st. dev. 8.1), all statistically significantly greater than the average number of co-defendants in Mom & Pop groups. 8 [INSERT FIGURE ABOUT HERE] These results are important for several reasons. They show that very few individuals across larger organized crime groups are being prosecuted. The number of co-defendants in Mom & Pop groups and Crime Rings is much closer to the total number in the entire group than those cases that involve larger organizations. Furthermore, prosecutions of individuals in larger organizations do not often include the high-ranking leaders in those groups, but instead typically involve lower-level members. Ultimately, these results reveal not only that the majority of human trafficking organized crime cases being federally prosecuted involve relatively small groups, but also that, even among groups that are very large in size, very few members within those groups are held accountable and those that are tend to be lower-ranking members of the group. [INSERT FIGURE ABOUT HERE] Next, we examine the scope of organized crime groups. 9 Per the typology, the two types of groups that are distinctive in terms of their scope are Street Gangs and Cartels/Mafias/Syndicates. Street Gangs operate either locally or nationwide (but not internationally). The results show that 43% (n = 26) of Street Gangs prosecuted in these cases operate locally and 57% (n = 35) are national. Cartels/Mafias/Syndicates operate only internationally. The remaining three organized crime group types may have a scope of operations that is local, national, or international. Thirty-seven percent (n = 49) of Mom & Pops operate locally only, as do just over half of crime rings (56%; n = 149). The majority of Illegal Enterprises operate internationally (63%; n = 65), and another 21% operate nationally (n = 22). Overall, 41% of federally prosecuted human trafficking cases involving organized crime involve groups operating solely within a single state. These cases could have been handled by state attorneys general or local district attorneys, potentially freeing up federal resources to focus on more complex, multi-jurisdictional trafficking networks that span state lines or national borders. [INSERT FIGURE 5 ABOUT HERE] Third, we examine the level of sophistication among the organized crime groups engaged in human trafficking as reflected in federally prosecuted cases. By definition, per the 5-S classification, Cartels/Mafias/Syndicates and Illegal Enterprises are highly sophisticated organizations, representing a complex and diversified criminal portfolio. These groups comprise only 21% (n = 133) of all federally prosecuted cases involving organized crime. Mom & Pop, Crime Rings, and Street Gangs can all vary in their level of complexity. We find that over 60% of both Mom & Pop and Crime Ring organizations have low levels of sophistication, and these are the two crime group types most prosecuted. This is in contrast to Street Gangs for whom over 85% have either medium or high levels of sophistication but constitute only 10% of prosecutions. In other words, the majority of federal human trafficking prosecutions involving organized crime groups focus on the least sophisticated types of organizations. This potentially reflects a reactive posture focused on what is most visible and prosecutable, rather than what may pose the greatest long-term threat. It also indicates a potential mismatch between enforcement effort and trafficking impact. More complex organizations often have broader reach, deeper networks, and greater capacity for sustained exploitation, yet they appear infrequently in the prosecution data. This could signal either detection challenges, capacity constraints, or strategic prioritization that leaves the most dangerous trafficking infrastructures relatively intact. [INSERT FIGURE 6 ABOUT HERE] The fourth S in the 5-S typology is structure, which examines the level of decentralization or hierarchy in the organizational structure. By definition, Crime Rings are extremely decentralized, while Cartels/Mafias/Syndicates are extremely hierarchical. The other three group types may vary in their organizational structures. However, the violin plot reveals that Mom and Pop organizations are as statistically decentralized as Crime Rings are. Street Gangs and Illegal Enterprises, on the other hand, also share similarities in terms of organizational structure with the majority being more centralized and hierarchical. In fact, Mom & Pop and Crime Rings are significantly more decentralized than Street Gangs and Illegal Enterprise (p < 0.01 for all). These findings show that federally prosecuted human trafficking cases involving organized crime disproportionately focus on groups that are more diffuse and decentralized. This suggests a pattern in which U.S. federal law enforcement may be more equipped—either legally, operationally, or resourced—to pursue loosely organized trafficking operations rather than deeply structured criminal enterprises. The decentralized nature of most prosecuted groups may reflect the relative ease of building cases against smaller, less coordinated entities. It may also indicate a structural blind spot wherein highly organized, hierarchical trafficking networks—such as those operating transnationally or with extensive criminal portfolios—are either harder to detect, harder to dismantle, or simply under-prioritized within the current enforcement paradigm. As a result, prosecutions may unintentionally create a distorted picture of the trafficking landscape, overrepresenting the types of groups that are more vulnerable to detection while underrepresenting those that are more deeply embedded, protected, and scalable. [INSERT FIGURE 7 ABOUT HERE] Finally, Self-Identification is determined by two criteria: 1) if a group has a self-ascribed name; and 2) the nature of the relationship among the members. 10 Mom and Pop and Crime Rings never have a name, while street gangs and illegal enterprises always do. Cartels/Mafias/Syndicates may have a name, but not always, although the data show that 75% (n = 15) do. Self-identification through name can play different roles for different groups. Regarding the nature of the relationship, Mom and Pop groups are always family or friends. The most common type of relationship among members of Crime Rings and Illegal Enterprises is accomplices, with 81% (n = 223) for Crime Rings and 36% ( n = 36) for Illegal Enterprises. Street Gangs are most often affiliated by a shared race/ethnicity (52%, n = 31), as are Cartels/Mafias/Syndicates (52%, n = 11). These elements of self-identification matter for several reasons. The presence of a self-ascribed name and shared identity for Street Gangs and many Cartels reflects a level of internal cohesion and collective identity that often correlates with more structured and enduring criminal operations. Further, a group that adopts a name and is organized around a common identity (e.g., race, ethnicity, gang affiliation) may be more likely to see itself as a durable criminal entity rather than a temporary collaboration. This has implications for how these groups recruit, expand, and persist over time, as well as how they may respond to enforcement pressure. On the other hand, groups like Mom & Pop and Crime Rings, which lack a name and are based on close personal relationships or loose criminal ties, may not self-identify as organized crime, and would likely resist that label. This ambiguity in identity can shape prosecutorial decisions whereby these types of groups may be easier to prosecute under general criminal statutes but harder to frame as part of broader organized crime efforts. While the descriptive analysis of the 5-S typology offers valuable insight into federal enforcement patterns and the structural characteristics of organized crime groups engaged in human trafficking, it does not tell us which types of trafficking these groups are involved in. To address this, we conducted a series of bivariate multinomial logistic regression analyses to examine the relationship between group typology and trafficking type. The results are in Table 2 wherein each row in the table is a bivariate model between the independent and dependent variables to avoid suppression effects due to high multicollinearity between the 5-S variables. The models compared three trafficking categories: minor sex trafficking, adult sex trafficking, and labor trafficking. The results reveal several important distinctions. First, group size did not significantly differ across trafficking types. In other words, large and small groups are equally as likely to engage in all three types of human trafficking. Further, we found no statistically significant differences in organizational structure (e.g., hierarchy vs. decentralization) across trafficking types, indicating that hierarchy alone does not distinguish which types of trafficking a group engages in. However, both size and structure may still play a role in shaping how enforcement agencies interpret and approach different cases—particularly when structure is coupled with other variables such as sophistication or self-identification. [INSERT Table 2 ABOUT HERE] On the other hand, significant differences in likelihood of engaging in different types of trafficking emerged for scope, sophistication, and self-identification. Organizations with narrower geographic scope are significantly more likely to engage in minor sex trafficking compared to adult sex trafficking (p < 0.01). This narrower operational footprint may explain, in part, why minor sex trafficking is overrepresented in federal prosecutions; these smaller, more localized groups may be easier to detect and prosecute using traditional investigative methods focused on regional or jurisdictional activity. In contrast, groups with broader geographic scope are significantly more likely to engage in labor trafficking than either minor and adult sex trafficking (p < 0.01). This finding implies that labor trafficking networks may be more difficult to disrupt, requiring multi-jurisdictional collaboration and cross-border investigative capacity that go beyond the scope of localized enforcement strategies. In terms of sophistication, less sophisticated groups are significantly more likely to engage in minor sex trafficking than either labor and adult sex trafficking (p < 0.01). This lower sophistication likely contributes to their higher prosecutorial visibility: simpler operational models are easier to detect, document, and dismantle, which may skew enforcement patterns toward these cases. Conversely, the higher sophistication of labor trafficking groups suggests a need for enhanced investigative tools and strategic intelligence gathering that can uncover complex, often opaque trafficking schemes. Finally, groups with family ties and stronger self-identification, including operating under a shared group name, are significantly more likely to be engaged in labor trafficking than either adult or minor sex trafficking. (p < 0.01). This degree of internal cohesion may create unique enforcement challenges, as family-based organizations often rely on trust, loyalty, and shared cultural norms to sustain operations. In contrast, groups with weaker identity ties and internal cohesion–those more likely to engage in minor and adult sex trafficking–may be more vulnerable to fragmentation and thus easier to investigate and prosecute. [INSERT FIGURE 8 ABOUT HERE] In addition to analyzing the type of trafficking in which organized crime groups engage based on the 5-S, we also examine this question based on the typological categories. We find that, across all typological categories except illegal enterprises, minor sex trafficking was the most common form of sex trafficking, ranging from 46% of all Mom & Pop cases to 89% of all Street Gang cases. This result is simply a function of there being over double the number of sex trafficking prosecutions than labor trafficking or adult sex trafficking combined. The most common type of human trafficking committed by Illegal Enterprises was labor trafficking (37%). Labor trafficking was also the second most common form of trafficking for Mom & Pop groups (32%), mostly a reflection of domestic servitude cases. On the other hand, labor trafficking comprises less than 2% of cases for Crime Rings and Street Gangs, with zero labor trafficking case among Cartels/Mafias/Syndicates. Adult sex trafficking was the second most common form of trafficking for Crime rings (19%), Street Gangs (6%), Cartels/Mafias/Syndicates (14%), and Illegal Enterprises (30%). [INSERT Table 3 ABOUT HERE] Examining these findings through a series of bivariate multinomial regressions allows for a more contextual analysis. Mom & Pop organizations were more likely to engage in labor trafficking when compared to both adult and minor sex trafficking (p < 0.001), again most likely reflecting cases involving domestic servitude. On the other hand, crime rings were significantly less likely to engage in labor trafficking than either type of sex trafficking (p < 0.001). Street Gangs were significantly more likely to engage in sex trafficking of a minor victim than either adult sex trafficking (p < 0.05) or labor trafficking (p < 0.1). Cartels were not significantly more likely to engage in any type of trafficking over another, although these results are most likely due to the very small number of cases in the dataset. Finally, Illegal Enterprises were somewhat more likely to engage in labor trafficking than adult sex trafficking (p < 0.1) and significantly more likely to engage in labor trafficking and adult sex trafficking than minor sex trafficking (p < .001). Together, these findings reinforce the need for tailored anti-trafficking enforcement strategies that account for key differences in organizational structure, sophistication, scope, and social dynamics across trafficking types. Failing to differentiate risks over-targeting low-complexity, high-visibility groups while allowing more complex and resilient trafficking networks to persist undetected. Discussion This study set out to systematically investigate the intersection of organized crime and human trafficking in the United States using an original 5-S typology based on size, scope, sophistication, structure, and self-identification. Drawing from a comprehensive dataset of over 2,390 federally prosecuted human trafficking cases from 2000 to 2022, we find that the majority of these cases (67%) involve unorganized operations, rather than organized criminal groups. Among the 635 cases that did involve organized crime, the overwhelming majority were classified as either small-scale "mom & pop" operations or decentralized "crime rings," rather than highly structured cartels, mafias, or syndicates. However, important differences emerged across trafficking types: minor sex trafficking cases were the least likely to involve organized groups and, when they did, the groups were typically smaller, less sophisticated, and more localized. In contrast, labor trafficking cases were significantly more likely to involve groups with broader geographic scope, higher sophistication, and stronger internal cohesion, often resembling illegal enterprises. Adult sex trafficking cases tended to occupy a middle ground, displaying greater organizational complexity than minor sex trafficking but generally less than labor trafficking. These distinctions highlight the need for differentiated policy and enforcement strategies tailored to the organizational characteristics of specific forms of trafficking. These findings carry important implications for policy and law enforcement. First, they suggest that a one-size-fits-all approach to combating human trafficking is likely to be ineffective. Policies and enforcement strategies must be calibrated to the organizational characteristics of the specific type of trafficking being addressed. Minor sex trafficking, which often involves loosely organized individuals or small informal groups, may require a stronger focus on local-level interventions, community-based detection, and early prevention efforts. By contrast, labor trafficking cases—where groups tend to be more sophisticated, structured, and geographically expansive—may demand broader inter-agency collaboration, international cooperation, financial crimes expertise, and specialized investigative units capable of dismantling complex criminal enterprises. The tendency to frame all trafficking as the work of large, transnational organized crime groups risks misdirecting resources and obscuring the real operational structures that must be disrupted. A more differentiated, evidence-based understanding of trafficking networks could lead to more effective prosecution strategies, more precise allocation of resources, and ultimately, greater protection for victims. Second, the results suggest that federal human trafficking prosecutions overwhelmingly involve smaller, less sophisticated operations. This may partially reflect law enforcement priorities and capacities, as it is arguably easier to detect and prosecute lower-tier organizations compared to complex, disciplined, and elusive criminal enterprises. Nevertheless, it challenges the dominant narrative, originating with the Palermo Protocol, that human trafficking is predominantly driven by large, transnational organized crime groups. Third, the findings highlight a potential misalignment between how human trafficking is conceptualized internationally and how it manifests domestically, at least in prosecuted cases. Policy, law enforcement strategies, and resource allocation premised on combating cartel-level trafficking operations may miss the realities on the ground: that trafficking is often carried out by smaller networks whose operations, while organized, are less hierarchical, less transnational, and less sophisticated than previously assumed. Finally, the study draws attention to potential selection bias inherent in using prosecuted cases as the basis for empirical analysis. It is likely that the most sophisticated trafficking operations evade detection and prosecution more effectively than smaller groups. Thus, while our findings are robust within the universe of federal prosecutions, they may not capture the full spectrum of organized criminal involvement in trafficking across the United States. Future research should aim to extend this analysis in several ways. First, scholars should seek to incorporate intelligence data, victim service provider reports, and qualitative interviews with law enforcement to triangulate and validate these findings beyond prosecuted cases. Additionally, comparative research across countries or regions would provide valuable insights into whether the patterns identified here are unique to the United States or represent broader global trends. Further, longitudinal studies would help determine whether the structure of trafficking organizations is evolving in response to policy interventions, technological advances, or shifting enforcement priorities. Ultimately, this study underscores the need for greater definitional clarity and empirical evidence when analyzing the organized crime and human trafficking nexus. By refining our understanding of how traffickers organize, we can better target strategies to disrupt these networks and protect vulnerable populations. Declarations Author Contribution V.B. developed the conceptual framework and coding schema, collected all data, and wrote the main manuscript text. S.V.D. conducted analyses and wrote the findings. Data Availability Please contact Allies Against Slavery for data requests. References U.S.C, § (2023) 371 https://www.law.cornell.edu/uscode/text/18/371 Abadinsky H (2010) Organized crime, 9th edn. Wadsworth/Cengage Learning Albanese JS (2011) Transnational crime and the 21st century: Criminal enterprise, corruption, and opportunity. Oxford University Press Aronowitz A, Veldhuizen M (2021) The human trafficking–organized crime nexus. In: Allum F, Gilmour S (eds) Routledge handbook of transnational organized crime. Routledge, pp 232–252 Bruckert C, Parent C (2002) Trafficking in human beings and organized crime: A literature review (pp. 1–35). Ottawa: Research and Evaluation Branch, Community, Contract and Aboriginal Policing Services Directorate, Royal Canadian Mounted Police. https://documentation.lastradainternational.org/lsidocs/bruckert_02_crime_0708.pdf Bruckert C, Parent C (2004) Organized crime and human trafficking in Canada: Tracing perceptions and discourses . Research and Evaluation Branch, Community, Contract and Aboriginal Policing Services Directorate, Royal Canadian Mounted Police. https://publications.gc.ca/Collection/PS64-1-2004E.pdf Bruggeman W (2002), September Illegal immigration and trafficking in human beings seen as a security problem for Europe. In European Conference on Preventing and Combating Trafficking in Human Beings , Brussels (pp. 18–20) Bruinsma GJN, Meershoek G (1999) Organized crime and trafficking in women from Eastern Europe in the Netherlands. In Illegal Immigration and Commercial Sex: The New Slave Trade (pp. 105–118). Routledge. https://doi.org/10.4324/9780203044551-5 Cabin RJ, Mitchell RJ (2000) To Bonferroni or not to Bonferroni: When and how are the questions. Bull Ecol Soc Am 81(3):246–248. http://www.jstor.org/stable/20168454 DeStefano A (2019) The war on human trafficking: US policy assessed. Rutgers University Press Finckenauer JO (2001) Russian transnational organized crime and human trafficking. Johns Hopkins University Finckenauer JO (2005) Problems of definition: What is organized crime? Trends Organized Crime 8:63–83. https://doi.org/10.1007/s12117-005-1038-4 Finckenauer JO, Schrock J (2000) Human trafficking: A growing criminal market in the U.S. In Human Trafficking: Data and Documents - Interdisciplinary Conference on Human Trafficking at the University of Nebraska (pp. 1–4). https://digitalcommons.unl.edu/humtraffdata/14 Gozdiak EM (2011) Data and research on human trafficking: Bibliography of research-based literature. DIANE Publishing Hagan FE (1983) The Organized crime continuum: A further specification of a new conceptual model. Criminal Justice Rev 8(2):52–57. https://doi.org/10.1177/073401688300800209 Hlavac M (2022) stargazer: Well-formatted regression and summary statistics tables [R package]. Social Policy Institute. https://CRAN.R-project.org/package=stargazer Lee M (2011) Trafficking and Global Crime Control. Sage, Los Angeles Maltz M (1985) Toward defining organized crime. In: Alexander HE, Caiden G (eds) The politics and economics of organized crime. D.C. Heath, pp 21–35 Maltz M (1994) Defining organized crime. In: Kelly RJ, Chin K-L, Schatzberg R (eds) Handbook of organized crime in the United States. Greenwood Omnibus Crime Control and Safe Streets Act of (1968) Pub. L. No. 90–351, 82 Stat. 197 (1968) Organized Crime Control Act of (1970) Pub. L. No. 91–452, 84 Stat. 922 (1970) Picarelli JT (2009) Organised crime and human trafficking in the United States and Western Europe. Strategies Against Hum Trafficking: Role Secur Sect, 134 Richard AON (1999) International trafficking in women to the United States: A contemporary manifestation of slavery and organized crime. Center for the Study of Intelligence R Core Team (2025) foreign: Read data stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase' (Version 0.8–90) [R package]. https://CRAN.R-project.org/package=foreign RStudio Team (2025) RStudio: Integrated development environment for R (Version 2025.05.0) [Computer software]. RStudio, PBC. https://posit.co Schloenhardt A (2001) Trafficking in migrants: Illegal migration and organized crime in Australia and the Asia Pacific region. Int J Sociol Law 29(4):331–378. https://doi.org/10.1006/ijsl.2001.0155 Shelley L (2003) Trafficking in women: The business model approach. Brown J World Affairs 10:119–131 Shelley L (2010) Human trafficking: A global perspective. Cambridge University Press, New York UN General Assembly (2001), January 8 United Nations Convention against Transnational Organized Crime: Resolution adopted by the General Assembly (A/RES/55/25) Väyrynen R (2005) Illegal immigration, human trafficking and organized crime. Poverty, international migration and asylum. Palgrave Macmillan UK, London, pp 143–170 Venables WN, Ripley BD (2002) MASS: Modern applied statistics with S [R package]. https://CRAN.R-project.org/package=MASS Weitzer R (2011) Sex trafficking and the sex industry: The need for evidence-based theory and legislation. J Crim L Criminol 101:1337. https://scholarlycommons.law.northwestern.edu/jclc Weitzer R (2014) New directions in research on human trafficking. ANNALS Am Acad Political Social Sci 653(1):6–24. https://doi.org/10.1177/0002716214521562 Williams P (2002) Transnational organized crime and the state. In: Hall RB (ed) The emergence of private authority in global governance. Cambridge University Press, pp 161–182 Williams P (2008) Trafficking in women: The role of transnational organized crime. In: Newman E, Cameron S (eds) Trafficking in humans. United Nations University Woodiwiss M, Hobbs M (2007) Organized evil and the Atlantic Alliance: Moral panics and the rhetoric of organized crime policing in America and Britain. Br J Criminol 49(1):106–128. https://doi.org/10.1093/bjc/azn054 Wickham H (2007) Reshaping data with the reshape package. J Stat Softw 21(12):1–20. http://www.jstatsoft.org/v21/i12/ Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019) Welcome to the tidyverse. J Open Source Softw 4(43):1686. 10.21105/joss.01686 Wickham H (2023) forcats: Tools for working with categorical variables (factors) (Version 1.0.0) [R package]. https://github.com/tidyverse/forcats https://forcats.tidyverse.org/ Wilke C (2024) ggridges: Ridgeline plots in 'ggplot2' (Version 0.5.6) [R package]. https://wilkelab.org/ggridges/ Zhang S (2012) Measuring labor trafficking: A research note. Crime Law Social Change 58:469–482. https://doi.org/10.1007/s10611-012-9393-y Zhang SX (2022) Progress and challenges in human trafficking research: Two decades after the Palermo Protocol. J Hum Trafficking 8(1):4–12. https://doi.org/10.1080/23322705.2021.2019528 Zeileis A, Hothorn T (2002) Diagnostic checking in regression relationships. R News 2(3):7–10. https://CRAN.R-project.org/doc/Rnews/ Zeileis A, Köll S, Graham N (2020) Various versatile variances: An object-oriented implementation of clustered covariances in R. J Stat Softw 95(1):1–36. https://doi.org/10.18637/jss.v095.i01 Footnotes In her discussion of the crime framing of the UN Trafficking Protocol, Lee ( 2011 ) states, “This enforcement orientation is reflected in the emphasis placed on the criminal justice provisions (which are obligatory for states ratifying the Trafficking Protocol) as opposed to the relatively weak language on the rights and assistance needs of trafficking victims (where the relevant articles are optional)” (p. 83). See Finckenauer ( 2005 ) for an excellent review of definitions of organized crime, and the distinction between organized crime, criminal organizations, and crime that is organized. For a brief description and comparison of the Shelley ( 2003 ) and Williams ( 2008 ) typologies, see Lee ( 2011 : 89–90). It is important to note that not all the cases in the database have defendants that are charged under 18 USC Chap. 77 on Peonge, Slavery, and Trafficking in Persons. All of the cases are human trafficking cases, but not all of the cases were necessarily prosecuted as human trafficking cases. All cases are coded by two people, an initial coder and a reviewer. Discrepancies are discussed and resolved to ensure reliability and accuracy of the data. Minor sex trafficking was defined as any sex trafficking case that involved at least one minor victim, even if the case also involved adult victims. 163 cases (7%) do not have enough information to make an organization determination. The standard deviations are very large across all averages, which means that there is significant variability in the number of co-defendants prosecuted within each organized crime group type. 55 cases did not have adequate information to infer a group’s scope. Family, Family/Friends, Friends, Race/Ethnicity, Accomplices, Tables Table 2 Bivariate multinomial logistic regressions predicting the likelihood of sex trafficking of an adult victim, sex trafficking of a minor victim, or labor trafficking based on organized crime dimension. Comparison Category - Adult Sex Trafficking Comparison Category - Minor Sex Trafficking Sex Trafficking of a Minor Victim Labor Trafficking Labor Trafficking Size 0.089 (0.169) -0.427 (0.253) -0.516 (0.217) Scope -0.705*** (0.149) 0.793*** (0.212) 1.499*** (0.188) Sophistication -0.519*** (0.152) 0.162 (0.188) 0.681*** (0.157) Structure -0.275 (0.114) -0.066 (0.146) 0.209 (0.118) Self-Identification Name Family Strength -0.466 (0.253) -0.459 (0.365) -0.045 (0.145) 0.556 (0.310) 1.873*** (0.380) 0.717*** (0.190) 1.022*** (0.253) 2.332*** (0.293) 0.762*** (0.155) * p < = 0.1, ** p < = 0.05, *** p < = 0.01 p-values adjusted through Bonferroni correction Table 3 Bivariate multinomial logistic regressions predicting the likelihood of sex trafficking of an adult victim, sex trafficking of a minor victim, or labor trafficking based on organized crime group type. Comparison Category - Adult Sex Trafficking Comparison Category - Minor Sex Trafficking Sex Trafficking of a Minor Victim Labor Trafficking Labor Trafficking Mom & Pop -0.105 (0.282) 1.511*** (0.325) 1.616*** (0.253) Crime Ring 0.440 (0.211) -3.005*** (0.544) -3.445*** (0.522) Street Gang 1.517** (0.529) -1.136 (1.127) -2.653* (1.016) Cartel/Mafia/Syndicate 0.474 (0.639) -6.877 (20.390) -8.381 (34.106) Illegal Enterprise -1.681*** (0.286) 0.777* (0.296) 2.457*** (0.291) * p < = 0.1, ** p < = 0.05, *** p < = 0.01 p-values adjusted through Bonferroni correction Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6597507","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454397141,"identity":"22735d99-473b-4c55-97d8-3a8b4180a20f","order_by":0,"name":"Vanessa Bouche","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYBADOQMgwQzjHSBGizGalgTCWhI3IGthwKfF4PjZgw9//LFL387eY/i5oMLOXr69+eGBnz9s7BnYDx/dgE3LmbxkY9625NydPWeMpWecSU7ccOaYwcGehLTEBp60tBtYtEg25JhJMzYw5264kWPGzNvGnGAgkcNwgCfhcAKDBI8ZVi39b8x//vhTn24A1vKv3l5+Rg7DwT8J/+1xaeGXyDFj4GE7nADR0nCYseFGDsNhnoQDjA04tbwxluZtO264s+dYsTTPseNgvxyWSUtObMPhFzb+HMOPP/5Uy5uzN2/8zFNTDQqxxx/f2NjZ87MfPoZNCx7ARpryUTAKRsEoGAVIAADSsWQ/oQBN3wAAAABJRU5ErkJggg==","orcid":"","institution":"Allies Against Slavery","correspondingAuthor":true,"prefix":"","firstName":"Vanessa","middleName":"","lastName":"Bouche","suffix":""},{"id":454397142,"identity":"88fdba62-0ab8-469c-acaf-ea07425f189d","order_by":1,"name":"Sarah Van Dyk","email":"","orcid":"","institution":"Vanderbilt University","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"Van","lastName":"Dyk","suffix":""}],"badges":[],"createdAt":"2025-05-05 22:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6597507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6597507/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82605776,"identity":"3895c231-49cd-4c70-8ae2-e04f85e40bde","added_by":"auto","created_at":"2025-05-13 10:03:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":167742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Typology Histogram\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/7382155f391c7c0a4751eb77.png"},{"id":82607062,"identity":"2ff3e06b-21e9-4c05-8c0c-19f6a4ed3c32","added_by":"auto","created_at":"2025-05-13 10:11:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":142833,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSize of Organization by Typology\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/1ceac5cbf5dd8a8e52da366c.png"},{"id":82605775,"identity":"9fcb9095-a923-47d6-b5a6-54ab97250c2f","added_by":"auto","created_at":"2025-05-13 10:03:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":154804,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of Defendants per Case by Crime Typology - Ridgeline\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Graph cut at 15 defendants for clarity\u003c/em\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/9c1c9d1993b8a0c4b8bfaae7.png"},{"id":82605778,"identity":"6607b2b9-6897-4e7f-adf9-96e75cde9ef1","added_by":"auto","created_at":"2025-05-13 10:03:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":158889,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScope by Crime Typology\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/5b18f2917f5dbd25e4cb455f.png"},{"id":82607711,"identity":"ca0843b2-6e7f-41b7-a66a-7be4da28b969","added_by":"auto","created_at":"2025-05-13 10:19:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":159065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSophistication by Crime Typology\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/d7168a593ad78d90deb1dfca.png"},{"id":82605784,"identity":"b5c5ff04-ce46-444d-9a65-b8c3928b406e","added_by":"auto","created_at":"2025-05-13 10:03:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":158777,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructure by Crime Typology\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/e6259d5ada77616f9ea3926f.png"},{"id":82607714,"identity":"eb0ad5eb-0bcb-4bb1-ab76-8abe80e45933","added_by":"auto","created_at":"2025-05-13 10:19:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":255327,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelf-Identification (Name) by Crime Typology\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/e6c8f759ae9b43e798f00f2e.png"},{"id":82607066,"identity":"cd6ce04a-662e-4856-9c59-8971c91d2ccc","added_by":"auto","created_at":"2025-05-13 10:11:32","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":205738,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOrganized Criminal Organization Type by Trafficking Crime\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/2452a8a79b8f1a5caeedd197.png"},{"id":86408054,"identity":"2f33731d-78c9-49a0-949b-b2dda291b093","added_by":"auto","created_at":"2025-07-10 10:09:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2330355,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6597507/v1/9e88e468-a53c-496c-8c31-c21f3a82c5ec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Organized Crime and Human Trafficking in the United States","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2000, the United Nations set forth the \u0026ldquo;Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children\u0026rdquo;. There are several aspects of this protocol that framed the issue of human trafficking for the international community. Perhaps most notably, the Protocol took a distinctively crime-centered approach, and more specifically couched human trafficking in terms of transnational organized crime.\u003csup\u003e1\u003c/sup\u003e The Protocol was signed as part of the UN Convention on Transnational Organized Crime in Palermo, Sicily, \u0026ldquo;the epicenter of the old Italian Mafia, the most fabled and notorious criminal syndicate in the world\u0026rdquo; (DeStefano 2008: 28). This seminal international document, which defines human trafficking for the first time in an international context, places the issue squarely in the context of organized crime.\u003c/p\u003e \u003cp\u003eDuring the drafting of the Protocol, and in the immediate years thereafter, government bodies, international organizations, and scholars all espoused the idea that transnational organized crime was behind global trafficking in persons (e.g., Bruinsma and Meershoek \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Richard \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Bruggeman \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Williams \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A body of scholarship then developed around this framing. Some of this literature examines the role of organized crime in human trafficking in specific regions of the globe, including Western Europe (Picarelli \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), Russia (Finckenauer \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), Canada (Bruckert and Parent \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Bruckert and Parent \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), the United States (Picarelli \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Richard \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), and Australia and Asia Pacific (Schloenhardt \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Other scholarship points to the role of organized crime in human trafficking as it intersects with other global issues such as migration (V\u0026auml;yrynen \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), human smuggling (Aronowitz \u0026amp; Veldhuizen, 2022, p. 235) and globalization (e.g., Shelley \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e: 40\u0026ndash;49).\u003c/p\u003e \u003cp\u003eWhile this literature collectively articulates the complexity of transnational human trafficking in the twenty-first century, there are a few limitations. First, much of this research is devoid of a clear definition of organized crime, which is problematic on a few levels. Stating that human trafficking is an issue of organized crime, without clearly defining organized crime, is tautological. It is first necessary to define organized crime, then determine the ways in which groups engaged in the crime of human trafficking meet or do not meet with various features of that definition. A definition is also necessary because it \u0026ldquo;goes a long way toward determining how laws are framed, how investigations and prosecutions are conducted, how research studies are done, and, increasingly, how mutual legal assistance across national borders is or is not rendered\u0026rdquo; (Finckenauer \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: 68). In other words, defining organized crime in the study of human trafficking is necessary for both philosophical and practical reasons.\u003c/p\u003e \u003cp\u003eThe second limitation is a function of the first. The extant literature framing human trafficking as an organized crime issue lacks empirical rigor. This is not necessarily unique to this body of work. Indeed, many scholars have pointed out the need for more empirical rigor in human trafficking research in general (e.g., Weitzer \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhang \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and a review of 218 journal articles on human trafficking found that only 39 were based on empirical research while the remaining were non-empirical (Gozdiak \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). While progress has been made in recent years (Zhang \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), this lack of analytical rigor has also been used as a criticism against the claim that human trafficking is an organized crime issue: \u0026ldquo;This transnational organized crime framework has prevailed despite a lack of clear evidence of its applicability to the trafficking context or systematic analysis of criminal justice data on the profile of trafficking offenders\u0026rdquo; (Lee \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e: 84). In other words, much of the literature citing organized crime in human trafficking does so as a matter of fact when, in the absence of solid empirical testing, it is merely an untested assumption. These theoretical and empirical weaknesses ultimately serve to legitimize criticism regarding anti-trafficking policies and practices (e.g., Woodiwiss and Hobbs 2008).\u003c/p\u003e \u003cp\u003eThe purpose of the present paper is to begin correcting for some of these gaps. First, we define organized crime by setting forth the \u0026ldquo;5-S\u0026rdquo; framework, which categorizes different types of organized crime groups along five dimensions: size, scope, structure, self-identification, and sophistication. The way groups vary along these combinations of dimensions determines the type: mom \u0026amp; pop, crime ring, street gang, cartel/mafia/syndicate, or illegal enterprise.\u003c/p\u003e \u003cp\u003eNext, we examine over 2,390 different human trafficking cases prosecuted in the United States to determine the extent, manner, and type of organized criminal engagement in human trafficking in the United States. We find that the vast majority of federal human trafficking prosecutions do not involve any elements of what can be considered organized criminal activity. Further, the majority of prosecutions that can be characterized as organized crime appear to be much smaller operations than previously believed, with most being mom \u0026amp; pop. That does not mean they are not organized; indeed, these mom \u0026amp; pop groups can be highly sophisticated with an international scope of operations, but they are smaller networks that do not represent the stereotypical understanding of organized crime. Additionally, the results suggest that, while most groups can be characterized as mom \u0026amp; pop, there is significant variance in terms of scope and sophistication among groups engaged in different types of human trafficking. For instance, labor and adult sex trafficking organizations tend to be more sophisticated with a broader scope of operations than groups engaged in minor sex trafficking.\u003c/p\u003e \u003cp\u003eWhile this paper takes the first step to clearly set forth a definitional typology and then empirically decipher organized crime groups engaged in human trafficking, the conclusions must be placed in the appropriate context. At best, the results reflect what can be discerned about these groups based on information in cases that have been federally prosecuted. Of course, there is a universe of actors that have evaded federal law enforcement detection or for whom evidence is not strong enough to indict. It is not unreasonable to hypothesize that those who have gone completely undetected are organized crime groups with strict discipline and nodal structures that are larger and more complex networks than a mom \u0026amp; pop structure. In other words, conclusions reached based on data available through federal prosecutions may be unique to the types of groups that get prosecuted, and not necessarily to the larger universe of actors engaged in human trafficking.\u003c/p\u003e\n\u003ch3\u003eOrganized Crime \u0026 Human Trafficking\u003c/h3\u003e\n\u003cp\u003eOrganized crime is an elusive concept, so difficult to define that The Organized Crime Control Act of \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1970\u003c/span\u003e (P.L. 91\u0026ndash;452, 84 Stat. 922) itself did not define it. The United Nations Convention Against Transnational Organised Crime (2000) defined \u0026ldquo;an organised criminal group\u0026rdquo; in Article 2(a) as \u0026ldquo;a structured group of three or more persons, existing for a period of time and acting in concert with the aim of committing one or more serious crimes or offences established in accordance with the Convention, in order to obtain, directly or indirectly, a financial or other material benefit.\u0026rdquo; While this definition is useful for the purpose of informing international law, it is \u0026ldquo;a very broad, sort of least common denominator definition\u0026rdquo; (Finckenauer \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: 68).\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFinckenauer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: 65) combines dimensions of organized crime proposed by Hagan (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) and Maltz (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1985\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) and derives eight \u0026ldquo;dimensions and characteristics\u0026rdquo; of organized crime groups. These eight dimensions are: ideology, structure/organized hierarchy, continuity, violence/use of force or the threat of force, restricted membership/bonding, illegal enterprises, penetration of legitimate businesses, and corruption. Abadinsky (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e: 3) also sets forth eight attributes of organized crime groups: no political goals, hierarchical, limited or exclusive membership, unique subculture, perpetuates itself, willingness to use illegal violence, monopolistic, and explicit rules and regulations. These characteristics intersect with the Finckenauer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) attributes to produce a relatively comprehensive descriptive understanding of the factors that separate organized crime groups from other types of criminals.\u003c/p\u003e \u003cp\u003eThe Omnibus Crime Control and Safe Streets Act of \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1968\u003c/span\u003e (Pub. L. No. 90\u0026ndash;351, 82 Stat. 197) defined organized crime in large part based on the types of crimes in which these groups engage. It states:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOrganized crime means the unlawful activities of the members of a highly organized, disciplined association engaged in supplying illegal goods and services, including but not limited to gambling, prostitution, loan sharking, narcotics, labor racketeering, and other unlawful activities of members of organizations.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHuman trafficking fits nicely into this list of the types of activities in which organized crime groups engage, especially as it intersects with prostitution and labor racketeering. Thus, between the descriptions of the group-based characteristics of criminal organizations, and the crime-types described as those in which criminal organizations engage, it is not surprising that those writing about human trafficking in the early years after the passage of the Palermo Protocol couched human trafficking in terms of organized crime.\u003c/p\u003e \u003cp\u003eUsing this problem frame, scholars began to decipher between different types of organized crime groups engaging in human trafficking, but with an understanding that defining human trafficking as an \u0026ldquo;organized crime\u0026rdquo; can mean different things. \u0026ldquo;Traffickers may be individual entrepreneurs, small \u0026lsquo;mom and pop\u0026rsquo; operations, or sophisticated, organized rings. There is little consensus among those who have studied the problem as to the proportions of each of those types; nor with respect to their level of organization and sophistication\u0026rdquo; (Finckenauer and Schrock 2001: 2).\u003c/p\u003e \u003cp\u003eShelley (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) set forth a typology that includes different models for groups engaging in trafficking in persons: the natural resource model, trade and development, supermarket, violent entrepreneurs, and traditional slavery/modern technology. Williams (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) offered a typology of human trafficking groups that is slightly different. Rather than focusing on the different types of business models for engaging in human trafficking, he focuses on the different types of groups, which include opportunistic amateurs, transnational criminal organizations with broad portfolios of activity, traditional criminal organizations, ethnically-based trafficking organizations, and criminal controlled businesses.\u003csup\u003e3\u003c/sup\u003e A third typology was offered by Picarelli (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). He argues there are three broadly defined types of groups engaging in human trafficking:\u003c/p\u003e \u003cp\u003eThe first are small trafficking groups comprised mainly of a handful of entrepreneurial individuals. Second\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eare cooperatives comprised of individuals, small groups and even criminal organisations that combine specialised skills to form larger trafficking syndicates. Last are situations where one large criminal organisation controls all aspects of a trafficking network. (p. 116)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFinally, Albanese (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e: 54) frames a typology around what he calls a \u0026ldquo;criminal enterprise approach\u0026rdquo;. His typology includes recruiters, transporters, and exploiters who may be organized differently and who all have different goals (pp. 55\u0026ndash;56).\u003c/p\u003e \u003cp\u003eAll of these typologies of human trafficking organizations are helpful in that they begin to fill the vacuum of definitional clarity and paint a picture of the diversity of groups engaged in human trafficking. Where they are lacking, however, is in parsimony. Building on these extant typological frameworks, I propose the \u0026ldquo;5-S\u0026rdquo; typology of organized human trafficking groups operating in the United States.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e5-S Typology of Organized Crime\u003c/h2\u003e \u003cp\u003eThe 5-S typology of organized human trafficking groups is named for five attributes (all starting with the letter \u0026ldquo;s\u0026rdquo;) of organized crime groups: size, scope, sophistication, structure, and self-identification. Each of these attributes has been discussed in one form or another as key characteristics of organized crime groups. For example, Finckenauer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: 75) directly addresses issues of sophistication, structure, and self-identification, and many scholars have addressed the variance in group size and scope of operation. Thus, each attribute of the 5-S typology is not new; rather, it is organized in a way that is parsimonious, easily digestible, and useful for empirical analysis.\u003c/p\u003e \u003cp\u003eThe first \u0026ldquo;s\u0026rdquo; is size. This, of course, refers to the number of people that are \u0026ldquo;members\u0026rdquo; of the organized crime group. Implicit in the UN definition of organized crime is that size can vary dramatically. It states that an organized criminal group may be comprised of \u0026ldquo;three or more persons\u0026rdquo;. In the United States, 18 U.S.C. 371 defines conspiracy\u0026mdash;a charge commonly used in cases involving organized crime\u0026mdash;as an agreement between \u0026ldquo;two or more persons\u0026rdquo; to commit a criminal act. Both the UN definition of an organized criminal group and the U.S. federal definition of conspiracy indicate that organized crime groups can range from very small to very large. Thus, size is an ordinal variable that ranges from small, medium, large.\u003c/p\u003e \u003cp\u003eSecond is scope, which refers to the territorial range of the group\u0026rsquo;s operation. Organized crime groups operating in the United States may operate only in a specific locality (city or state), across state lines, or transnationally. It is important to note that much of the literature on organized crime groups has had a distinctive transnational focus. This may be the result of globalization and the factors that have made it easier to move goods and people illicitly around the globe. Indeed, \u0026ldquo;organized crime group\u0026rdquo; was defined in the UN Convention on \u003cem\u003eTransnational\u003c/em\u003e Organized Crime. However, to be considered an organized crime group, operating transnationally is neither a necessary nor a sufficient condition. Therefore, scope is a nominal variable that is coded: local, national, transnational.\u003c/p\u003e \u003cp\u003eSophistication is the third \u0026ldquo;s\u0026rdquo; in the 5-S typology. In describing sophistication, Finckenauer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e: 75) asks these questions: \u0026ldquo;What degree of planning is used in carrying out crimes? How long do individual criminal ventures last? How much skill and knowledge are required in carrying out these crimes?\u0026rdquo; I define sophistication as the complexity of the group\u0026rsquo;s organized criminal activities and the extent to which their portfolios are diversified. Shelley\u0026rsquo;s (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) \u0026ldquo;violent entrepreneurs\u0026rdquo; and \u0026ldquo;traditional slavery/modern technology\u0026rdquo; types would be considered more sophisticated under this definition as their criminal portfolio is heterogeneous, either as a means of carrying out their human trafficking activities (e.g., visa fraud, money laundering, etc.), or because they are engaged in crimes beyond trafficking in persons (e.g., drug trafficking or terrorism). On the other hand, Williams (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) \u0026ldquo;opportunistic amateurs\u0026rdquo; would be low in sophistication as their criminal portfolios are relatively homogeneous and the operating procedures are relatively simple. Sophistication is therefore an ordinal variable coded low, medium, high.\u003c/p\u003e \u003cp\u003eThe fourth \u0026ldquo;s\u0026rdquo; is structure, which refers to the extent to which the group is structured hierarchically or is decentralized. Many definitions of organized crime groups refer in some way to the organizational structure of the group, and specifically to the hierarchical nature of the groups (e.g., Abadinsky \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hagan \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Maltz \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1985\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Finckenauer \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). For example, Abadinsky (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e: 3) states, \u0026ldquo;An organized crime group has a vertical power structure with at least three permanent ranks\u0026mdash;not just a leader and followers\u0026mdash;each with authority over the level beneath.\u0026rdquo; However, other definitions do not view hierarchy as a necessary condition to defining an organized criminal group. In defining organized crime groups as being comprised of \u0026ldquo;a structured group of three or more persons,\u0026rdquo; the UN Convention on Transnational Organized Crime makes provision for all sorts of organizational structures beyond those that are hierarchical. Therefore, I argue that organized crime groups may vary in their structure, and I use an ordinal coding structure that includes: very decentralized, somewhat decentralized, somewhat hierarchical, very hierarchical.\u003c/p\u003e \u003cp\u003eFinally, the last \u0026ldquo;s\u0026rdquo; in the 5-S typology of organized crime groups refers to self-identification. Self-identification has two sub-categories: 1) name; and 2) type of identification. Name simply refers to whether or not a group has a proper name. This can be a gang name, such as Bloods, or a business name. Therefore, name is coded simply as yes or no.\u003c/p\u003e \u003cp\u003eType of self-identification refers to the identity around which the group is formed. For example, ethnicity has been a major identity around which government agencies and scholars have understood organized crime groups; however, ethnicity is not the only identity around which organized crime groups form. Albanese (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e: 5) refers to this as the \u0026ldquo;ethnicity trap\u0026rdquo; and argues that \u0026ldquo;the use of ethnicity as a descriptor of criminal activity is extremely limited.\u0026rdquo; Another type of self-identification can be region, biological family, prison groups, or motorcycle gangs. The key here is not the specific type of self-identification, but whether or not the group is organized around a common identifying characteristic beyond banding together to commit a criminal act. Thus, type of self-identification is a nominal variable with the following categories: family, friend, family/friend, race/ethnicity, accomplices, gang members.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e[INSERT TABLE 1 ABOUT HERE]\u003c/h3\u003e\n\u003cp\u003eVariance across the 5-S typology generates five different types of organized crime groups. The first type is \u0026ldquo;Mom \u0026amp; Pop.\u0026rdquo; This type of group is defined by size and self-identification. The size of a mom \u0026amp; pop group is small. Although it is difficult to put a firm number to the size, as a general matter, a mom \u0026amp; pop group would constitute less than 10 people. In addition to size, mom \u0026amp; pop groups are also defined by self-identification wherein the type of self-identification is family or friends with no proper name for the group. Mom \u0026amp; pop groups cannot be defined by sophistication, scope, or structure because they can vary dramatically in all three of these categories.\u003c/p\u003e \u003cp\u003eThe second type of group generated by the 5-S typology is \u0026ldquo;Crime Ring.\u0026rdquo; A crime ring is defined by its structure in that it must be extremely or somewhat decentralized with no boss or rigid hierarchy. Crime rings can also be differentiated from other groups in that the strength of self-identification as a group is weak, they are not organized around any particular type of identity such as race, ethnicity, or family, but rather as accomplices, and there is no proper name with which the group associates itself. Crime rings cannot be differentiated from other types of organized crime groups based on sophistication, scope, or size because crime rings can vary along these dimensions.\u003c/p\u003e \u003cp\u003e\u0026ldquo;Street Gang\u0026rdquo; is the third type of group generated by the 5-S typology, and street gangs are defined based on their scope and self-identification. In order to be classified as a street gang, the group must operate either locally or nationally. If a group operates transnationally, then it is not classified as a street gang. They are also distinct in their self-identification. The strength of their self-identification is strong, the type of self-identification is well-defined, and the name of the group is proper and distinct. Street gangs cannot be classified as such based on size, sophistication, or structure because all of these can be variable for these types of groups.\u003c/p\u003e \u003cp\u003eThe fourth classification is \u0026ldquo;Cartel/Mafia/Syndicate.\u0026rdquo; I use these three words interchangeably because they can all be classified based on the same set of criteria. First, these groups must be large, with hundreds or even thousands of members. Second, cartels/mafias/syndicates must have a transnational scope of operations. If they operate only in one location or one state, then they are not a cartel/mafia/syndicate. Third, these types of groups are highly sophisticated and have a heterogeneous portfolio of criminal activities. In terms of structure, these groups must be hierarchical with clear bosses or kingpins. Thus, cartels/mafias/syndicates may be defined as such based on size, scope, sophistication, and structure. Their self-identification, on the other hand, varies across strength, type, and name and cannot necessarily be used as a condition for classification.\u003c/p\u003e \u003cp\u003eThe final type is \u0026ldquo;Illegal Enterprise.\u0026rdquo; The defining characteristics of illegal enterprises are sophistication and self-identification. Illegal enterprises are highly sophisticated in that they engage in a variety of complex criminal activities. In setting up the illegal enterprise, these groups must often engage in a variety of conspiratorial acts against the government, including money laundering, tax evasion, document fraud, and extortion. Additionally, illegal enterprises can be classified as such based on self-identification wherein the type of identification is a business. Moreover, the name of the business is an official and proper name. Illegal enterprises vary on all other classification dimensions, including size, scope, and structure.\u003c/p\u003e \u003cp\u003eOverall, the 5-S typology is a parsimonious framework to understand the diversity of actors engaged in human trafficking in the United States and the dimensions on which they vary. The next two sections explain the methodology for collecting cases and provide the results of the analysis.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eIn order to examine the extent to which organized crime (as defined by the 5-S typology) is engaged in human trafficking in the United States, we examined all of the federally-prosecuted human trafficking cases across the United States from 2000 to 2022. Allies Against Slavery collects the cases by searching Bloomberg Law using a very specific keyword search protocol, which includes search terms relevant to different types of human trafficking, as well as search terms relevant to organized criminal cases, such as RICO, conspiracy, gang, organized crime, racketeering, mafia, cartel, or document fraud. After conducting the searches, the research team sorts the cases to discard false positives and ensure that the facts of the case clearly indicate human trafficking.\u003csup\u003e4\u003c/sup\u003e Finally, the research team downloads case documents\u0026ndash;docket reports, indictments, criminal complaints, and/or sentencing memoranda\u0026ndash;in order to stage the case in preparation for coding. The research team also conducts media searches using Access World News and Google News for each of the cases. Some cases have an abundance of news coverage, while others have none.\u003c/p\u003e \u003cp\u003eAfter collecting the cases, the research team begins the process of coding the cases in accordance with a very exhaustive and detailed case coding protocol.\u003csup\u003e5\u003c/sup\u003e Using the information contained in the case documents and news articles, key variables are extracted at the case level and the defendant level. At the case level, the research team codes for things like the state, federal district, and year of the prosecution, the type of human trafficking involved, the criminal methods used by the traffickers, crime locations and routes, and victim information including number of victims and their demographic characteristics (age, nationality, gender). At the defendant level, the research team extracts demographic information about the defendant (age at arrest, race/ethnicity, gender), and all charging and sentencing details. In addition, the team codes for organized crime using the 5-S typology in order to determine if the person or people involved in the case is/are acting in an unorganized manner, or can be classified as mom and pop, crime ring, street gang, cartel/mafia/syndicate, or illegal enterprise.\u003c/p\u003e \u003cp\u003eThe data was then analysed using RStudio (RStudio Team, 2023) and the packages tidyverse, lmtest, sandwich, stargazer, reshape2, ggridges, foreign, nnet, and forcats (Wickham et al 2009, Zeileis and Hothorn \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Zeileis et al \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Hlavac \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wickham \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, Wilke \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, R Core Team, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e, Venables and Ripley \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Wickham \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). First, summary statistics were calculated. Then we fit multiple bivariate multinomial logit regression models comparing labor and minor sex trafficking to adult sex trafficking, as well as adult sex trafficking and labor trafficking to minor sex trafficking to allow for comparison of each form of trafficking to each other form of trafficking.\u003csup\u003e6\u003c/sup\u003e Only cases with complete data across all independent and dependent variables were included (n\u0026thinsp;=\u0026thinsp;510). Given that repeated bivariate tests are associated with Type I error, we then adjusted p-values using the Bonferroni adjustment (Cabin and Randall 2000). Finally, we repeated the same process of fitting bivariate multinomial regression models using Bonferroni adjustments to compare the predicted probability of engagement in trafficking crime type based on crime group type. These were conducted where the independent variable was a binary variable of either being the group of interest (i.e. Mom \u0026amp; Pop) or all other groups.\u003c/p\u003e \u003cp\u003eThe dataset includes 2,390 federally prosecuted human trafficking cases from 2000 to 2022 involving a total of 4,557 defendants and 11,495 identified victims. Below, we present the results of the 5-S typology of organized crime and human trafficking in the United States as evidenced in federal human trafficking prosecutions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e details the distribution of organized crime classifications for all cases in the dataset. The first major finding is that, among federally prosecuted human trafficking cases, the majority (67%, n\u0026thinsp;=\u0026thinsp;1,592) are unorganized.\u003csup\u003e7\u003c/sup\u003e The differences in means between the total number of organized versus unorganized cases is statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In other words, federal investigators and prosecutors are spending a disproportionate amount of time and resources on cases that do not indicate any type of organized criminal activity per the 5-S typology.\u003c/p\u003e\n\u003ch3\u003e[INSERT FIGURE ABOUT HERE]\u003c/h3\u003e\n\u003cp\u003eThere are a total of 635 cases that can be classified as involving organized crime, which had a total of 2,381 defendants. Among those, a combined 69% are Crime Rings (48%; n\u0026thinsp;=\u0026thinsp;306) and Mom \u0026amp; Pop (21%; n\u0026thinsp;=\u0026thinsp;134). As we investigate the 5-S typology more deeply, it becomes clear that, while the majority of federal human trafficking prosecutions do not indicate any level of organized criminal activity at all, those that do mostly represent relatively small and unsophisticated types of organized crime groups.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT FIGURE \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eThe first S is size of the organization. It is important to note that the number of defendants in the case does \u003cem\u003enot\u003c/em\u003e necessarily indicate the total size of the group. For example, a Cartel/Mafia/Syndicate is extremely large, often with hundreds or thousands of members; however, it is possible that only one member of the Cartel/Mafia/Syndicate is a defendant in a case with no co-defendants. That said, the number of co-defendants generally does reflect the size of the group. Crime Rings have the lowest number of defendants per case at 3.0 (st. dev. 3.1) and Mom \u0026amp; Pop groups have the next lowest with 3.5 (st. dev. 3.0) defendants on average per case. These are also the two smallest types of organized crime groups, and the difference in means between them is not statistically significant. This is significantly different than the other organized crime group types. Illegal Enterprises have an average of 4.8 (st. dev. 4.8) defendants per case, Street Gangs have 5.4 (st. dev. 7.5), and Cartels/Mafias/Syndicates have 6.3 (st. dev. 8.1), all statistically significantly greater than the average number of co-defendants in Mom \u0026amp; Pop groups.\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e[INSERT FIGURE ABOUT HERE]\u003c/h3\u003e\n\u003cp\u003eThese results are important for several reasons. They show that very few individuals across larger organized crime groups are being prosecuted. The number of co-defendants in Mom \u0026amp; Pop groups and Crime Rings is much closer to the total number in the entire group than those cases that involve larger organizations. Furthermore, prosecutions of individuals in larger organizations do not often include the high-ranking leaders in those groups, but instead typically involve lower-level members. Ultimately, these results reveal not only that the majority of human trafficking organized crime cases being federally prosecuted involve relatively small groups, but also that, even among groups that are very large in size, very few members within those groups are held accountable and those that are tend to be lower-ranking members of the group.\u003c/p\u003e\n\u003ch3\u003e[INSERT FIGURE ABOUT HERE]\u003c/h3\u003e\n\u003cp\u003eNext, we examine the scope of organized crime groups.\u003csup\u003e9\u003c/sup\u003e Per the typology, the two types of groups that are distinctive in terms of their scope are Street Gangs and Cartels/Mafias/Syndicates. Street Gangs operate either locally or nationwide (but not internationally). The results show that 43% (n\u0026thinsp;=\u0026thinsp;26) of Street Gangs prosecuted in these cases operate locally and 57% (n\u0026thinsp;=\u0026thinsp;35) are national. Cartels/Mafias/Syndicates operate only internationally. The remaining three organized crime group types may have a scope of operations that is local, national, or international. Thirty-seven percent (n\u0026thinsp;=\u0026thinsp;49) of Mom \u0026amp; Pops operate locally only, as do just over half of crime rings (56%; n\u0026thinsp;=\u0026thinsp;149). The majority of Illegal Enterprises operate internationally (63%; n\u0026thinsp;=\u0026thinsp;65), and another 21% operate nationally (n\u0026thinsp;=\u0026thinsp;22). Overall, 41% of federally prosecuted human trafficking cases involving organized crime involve groups operating solely within a single state. These cases could have been handled by state attorneys general or local district attorneys, potentially freeing up federal resources to focus on more complex, multi-jurisdictional trafficking networks that span state lines or national borders.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT FIGURE \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eThird, we examine the level of sophistication among the organized crime groups engaged in human trafficking as reflected in federally prosecuted cases. By definition, per the 5-S classification, Cartels/Mafias/Syndicates and Illegal Enterprises are highly sophisticated organizations, representing a complex and diversified criminal portfolio. These groups comprise only 21% (n\u0026thinsp;=\u0026thinsp;133) of all federally prosecuted cases involving organized crime. Mom \u0026amp; Pop, Crime Rings, and Street Gangs can all vary in their level of complexity. We find that over 60% of both Mom \u0026amp; Pop and Crime Ring organizations have low levels of sophistication, and these are the two crime group types most prosecuted. This is in contrast to Street Gangs for whom over 85% have either medium or high levels of sophistication but constitute only 10% of prosecutions.\u003c/p\u003e \u003cp\u003eIn other words, the majority of federal human trafficking prosecutions involving organized crime groups focus on the least sophisticated types of organizations. This potentially reflects a reactive posture focused on what is most visible and prosecutable, rather than what may pose the greatest long-term threat. It also indicates a potential mismatch between enforcement effort and trafficking impact. More complex organizations often have broader reach, deeper networks, and greater capacity for sustained exploitation, yet they appear infrequently in the prosecution data. This could signal either detection challenges, capacity constraints, or strategic prioritization that leaves the most dangerous trafficking infrastructures relatively intact.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT FIGURE \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eThe fourth S in the 5-S typology is structure, which examines the level of decentralization or hierarchy in the organizational structure. By definition, Crime Rings are extremely decentralized, while Cartels/Mafias/Syndicates are extremely hierarchical. The other three group types may vary in their organizational structures. However, the violin plot reveals that Mom and Pop organizations are as statistically decentralized as Crime Rings are. Street Gangs and Illegal Enterprises, on the other hand, also share similarities in terms of organizational structure with the majority being more centralized and hierarchical. In fact, Mom \u0026amp; Pop and Crime Rings are significantly more decentralized than Street Gangs and Illegal Enterprise (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for all).\u003c/p\u003e \u003cp\u003eThese findings show that federally prosecuted human trafficking cases involving organized crime disproportionately focus on groups that are more diffuse and decentralized. This suggests a pattern in which U.S. federal law enforcement may be more equipped\u0026mdash;either legally, operationally, or resourced\u0026mdash;to pursue loosely organized trafficking operations rather than deeply structured criminal enterprises. The decentralized nature of most prosecuted groups may reflect the relative ease of building cases against smaller, less coordinated entities. It may also indicate a structural blind spot wherein highly organized, hierarchical trafficking networks\u0026mdash;such as those operating transnationally or with extensive criminal portfolios\u0026mdash;are either harder to detect, harder to dismantle, or simply under-prioritized within the current enforcement paradigm. As a result, prosecutions may unintentionally create a distorted picture of the trafficking landscape, overrepresenting the types of groups that are more vulnerable to detection while underrepresenting those that are more deeply embedded, protected, and scalable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT FIGURE \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eFinally, Self-Identification is determined by two criteria: 1) if a group has a self-ascribed name; and 2) the nature of the relationship among the members.\u003csup\u003e10\u003c/sup\u003e Mom and Pop and Crime Rings never have a name, while street gangs and illegal enterprises always do. Cartels/Mafias/Syndicates may have a name, but not always, although the data show that 75% (n\u0026thinsp;=\u0026thinsp;15) do. Self-identification through name can play different roles for different groups. Regarding the nature of the relationship, Mom and Pop groups are always family or friends. The most common type of relationship among members of Crime Rings and Illegal Enterprises is accomplices, with 81% (n\u0026thinsp;=\u0026thinsp;223) for Crime Rings and 36% ( n\u0026thinsp;=\u0026thinsp;36) for Illegal Enterprises. Street Gangs are most often affiliated by a shared race/ethnicity (52%, n\u0026thinsp;=\u0026thinsp;31), as are Cartels/Mafias/Syndicates (52%, n\u0026thinsp;=\u0026thinsp;11).\u003c/p\u003e \u003cp\u003eThese elements of self-identification matter for several reasons. The presence of a self-ascribed name and shared identity for Street Gangs and many Cartels reflects a level of internal cohesion and collective identity that often correlates with more structured and enduring criminal operations. Further, a group that adopts a name and is organized around a common identity (e.g., race, ethnicity, gang affiliation) may be more likely to see itself as a durable criminal entity rather than a temporary collaboration. This has implications for how these groups recruit, expand, and persist over time, as well as how they may respond to enforcement pressure. On the other hand, groups like Mom \u0026amp; Pop and Crime Rings, which lack a name and are based on close personal relationships or loose criminal ties, may not self-identify as organized crime, and would likely resist that label. This ambiguity in identity can shape prosecutorial decisions whereby these types of groups may be easier to prosecute under general criminal statutes but harder to frame as part of broader organized crime efforts.\u003c/p\u003e \u003cp\u003eWhile the descriptive analysis of the 5-S typology offers valuable insight into federal enforcement patterns and the structural characteristics of organized crime groups engaged in human trafficking, it does not tell us which types of trafficking these groups are involved in. To address this, we conducted a series of bivariate multinomial logistic regression analyses to examine the relationship between group typology and trafficking type. The results are in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e wherein each row in the table is a bivariate model between the independent and dependent variables to avoid suppression effects due to high multicollinearity between the 5-S variables. The models compared three trafficking categories: minor sex trafficking, adult sex trafficking, and labor trafficking.\u003c/p\u003e \u003cp\u003eThe results reveal several important distinctions. First, group size did not significantly differ across trafficking types. In other words, large and small groups are equally as likely to engage in all three types of human trafficking. Further, we found no statistically significant differences in organizational structure (e.g., hierarchy vs. decentralization) across trafficking types, indicating that hierarchy alone does not distinguish which types of trafficking a group engages in. However, both size and structure may still play a role in shaping how enforcement agencies interpret and approach different cases\u0026mdash;particularly when structure is coupled with other variables such as sophistication or self-identification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eOn the other hand, significant differences in likelihood of engaging in different types of trafficking emerged for scope, sophistication, and self-identification. Organizations with narrower geographic scope are significantly more likely to engage in minor sex trafficking compared to adult sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This narrower operational footprint may explain, in part, why minor sex trafficking is overrepresented in federal prosecutions; these smaller, more localized groups may be easier to detect and prosecute using traditional investigative methods focused on regional or jurisdictional activity. In contrast, groups with broader geographic scope are significantly more likely to engage in labor trafficking than either minor and adult sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This finding implies that labor trafficking networks may be more difficult to disrupt, requiring multi-jurisdictional collaboration and cross-border investigative capacity that go beyond the scope of localized enforcement strategies.\u003c/p\u003e \u003cp\u003eIn terms of sophistication, less sophisticated groups are significantly more likely to engage in minor sex trafficking than either labor and adult sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This lower sophistication likely contributes to their higher prosecutorial visibility: simpler operational models are easier to detect, document, and dismantle, which may skew enforcement patterns toward these cases. Conversely, the higher sophistication of labor trafficking groups suggests a need for enhanced investigative tools and strategic intelligence gathering that can uncover complex, often opaque trafficking schemes.\u003c/p\u003e \u003cp\u003eFinally, groups with family ties and stronger self-identification, including operating under a shared group name, are significantly more likely to be engaged in labor trafficking than either adult or minor sex trafficking. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This degree of internal cohesion may create unique enforcement challenges, as family-based organizations often rely on trust, loyalty, and shared cultural norms to sustain operations. In contrast, groups with weaker identity ties and internal cohesion\u0026ndash;those more likely to engage in minor and adult sex trafficking\u0026ndash;may be more vulnerable to fragmentation and thus easier to investigate and prosecute.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT FIGURE \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eIn addition to analyzing the type of trafficking in which organized crime groups engage based on the 5-S, we also examine this question based on the typological categories. We find that, across all typological categories except illegal enterprises, minor sex trafficking was the most common form of sex trafficking, ranging from 46% of all Mom \u0026amp; Pop cases to 89% of all Street Gang cases. This result is simply a function of there being over double the number of sex trafficking prosecutions than labor trafficking or adult sex trafficking combined. The most common type of human trafficking committed by Illegal Enterprises was labor trafficking (37%). Labor trafficking was also the second most common form of trafficking for Mom \u0026amp; Pop groups (32%), mostly a reflection of domestic servitude cases. On the other hand, labor trafficking comprises less than 2% of cases for Crime Rings and Street Gangs, with zero labor trafficking case among Cartels/Mafias/Syndicates. Adult sex trafficking was the second most common form of trafficking for Crime rings (19%), Street Gangs (6%), Cartels/Mafias/Syndicates (14%), and Illegal Enterprises (30%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e[INSERT Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e ABOUT HERE]\u003c/h2\u003e \u003cp\u003eExamining these findings through a series of bivariate multinomial regressions allows for a more contextual analysis. Mom \u0026amp; Pop organizations were more likely to engage in labor trafficking when compared to both adult and minor sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), again most likely reflecting cases involving domestic servitude. On the other hand, crime rings were significantly less likely to engage in labor trafficking than either type of sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Street Gangs were significantly more likely to engage in sex trafficking of a minor victim than either adult sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) or labor trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.1). Cartels were not significantly more likely to engage in any type of trafficking over another, although these results are most likely due to the very small number of cases in the dataset. Finally, Illegal Enterprises were somewhat more likely to engage in labor trafficking than adult sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;0.1) and significantly more likely to engage in labor trafficking and adult sex trafficking than minor sex trafficking (p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003cp\u003eTogether, these findings reinforce the need for tailored anti-trafficking enforcement strategies that account for key differences in organizational structure, sophistication, scope, and social dynamics across trafficking types. Failing to differentiate risks over-targeting low-complexity, high-visibility groups while allowing more complex and resilient trafficking networks to persist undetected.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study set out to systematically investigate the intersection of organized crime and human trafficking in the United States using an original 5-S typology based on size, scope, sophistication, structure, and self-identification. Drawing from a comprehensive dataset of over 2,390 federally prosecuted human trafficking cases from 2000 to 2022, we find that the majority of these cases (67%) involve unorganized operations, rather than organized criminal groups. Among the 635 cases that did involve organized crime, the overwhelming majority were classified as either small-scale \"mom \u0026amp; pop\" operations or decentralized \"crime rings,\" rather than highly structured cartels, mafias, or syndicates. However, important differences emerged across trafficking types: minor sex trafficking cases were the least likely to involve organized groups and, when they did, the groups were typically smaller, less sophisticated, and more localized. In contrast, labor trafficking cases were significantly more likely to involve groups with broader geographic scope, higher sophistication, and stronger internal cohesion, often resembling illegal enterprises. Adult sex trafficking cases tended to occupy a middle ground, displaying greater organizational complexity than minor sex trafficking but generally less than labor trafficking. These distinctions highlight the need for differentiated policy and enforcement strategies tailored to the organizational characteristics of specific forms of trafficking.\u003c/p\u003e \u003cp\u003eThese findings carry important implications for policy and law enforcement. First, they suggest that a one-size-fits-all approach to combating human trafficking is likely to be ineffective. Policies and enforcement strategies must be calibrated to the organizational characteristics of the specific type of trafficking being addressed. Minor sex trafficking, which often involves loosely organized individuals or small informal groups, may require a stronger focus on local-level interventions, community-based detection, and early prevention efforts. By contrast, labor trafficking cases\u0026mdash;where groups tend to be more sophisticated, structured, and geographically expansive\u0026mdash;may demand broader inter-agency collaboration, international cooperation, financial crimes expertise, and specialized investigative units capable of dismantling complex criminal enterprises. The tendency to frame all trafficking as the work of large, transnational organized crime groups risks misdirecting resources and obscuring the real operational structures that must be disrupted. A more differentiated, evidence-based understanding of trafficking networks could lead to more effective prosecution strategies, more precise allocation of resources, and ultimately, greater protection for victims.\u003c/p\u003e \u003cp\u003eSecond, the results suggest that federal human trafficking prosecutions overwhelmingly involve smaller, less sophisticated operations. This may partially reflect law enforcement priorities and capacities, as it is arguably easier to detect and prosecute lower-tier organizations compared to complex, disciplined, and elusive criminal enterprises. Nevertheless, it challenges the dominant narrative, originating with the Palermo Protocol, that human trafficking is predominantly driven by large, transnational organized crime groups.\u003c/p\u003e \u003cp\u003eThird, the findings highlight a potential misalignment between how human trafficking is conceptualized internationally and how it manifests domestically, at least in prosecuted cases. Policy, law enforcement strategies, and resource allocation premised on combating cartel-level trafficking operations may miss the realities on the ground: that trafficking is often carried out by smaller networks whose operations, while organized, are less hierarchical, less transnational, and less sophisticated than previously assumed.\u003c/p\u003e \u003cp\u003eFinally, the study draws attention to potential selection bias inherent in using prosecuted cases as the basis for empirical analysis. It is likely that the most sophisticated trafficking operations evade detection and prosecution more effectively than smaller groups. Thus, while our findings are robust within the universe of federal prosecutions, they may not capture the full spectrum of organized criminal involvement in trafficking across the United States.\u003c/p\u003e \u003cp\u003eFuture research should aim to extend this analysis in several ways. First, scholars should seek to incorporate intelligence data, victim service provider reports, and qualitative interviews with law enforcement to triangulate and validate these findings beyond prosecuted cases. Additionally, comparative research across countries or regions would provide valuable insights into whether the patterns identified here are unique to the United States or represent broader global trends. Further, longitudinal studies would help determine whether the structure of trafficking organizations is evolving in response to policy interventions, technological advances, or shifting enforcement priorities.\u003c/p\u003e \u003cp\u003eUltimately, this study underscores the need for greater definitional clarity and empirical evidence when analyzing the organized crime and human trafficking nexus. By refining our understanding of how traffickers organize, we can better target strategies to disrupt these networks and protect vulnerable populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eV.B. developed the conceptual framework and coding schema, collected all data, and wrote the main manuscript text. S.V.D. conducted analyses and wrote the findings.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003ePlease contact Allies Against Slavery for data requests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eU.S.C, \u0026sect; (2023) 371 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.law.cornell.edu/uscode/text/18/371\u003c/span\u003e\u003cspan address=\"https://www.law.cornell.edu/uscode/text/18/371\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbadinsky H (2010) Organized crime, 9th edn. Wadsworth/Cengage Learning\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlbanese JS (2011) Transnational crime and the 21st century: Criminal enterprise, corruption, and opportunity. 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J Stat Softw 95(1):1\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18637/jss.v095.i01\u003c/span\u003e\u003cspan address=\"10.18637/jss.v095.i01\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e In her discussion of the crime framing of the UN Trafficking Protocol, Lee (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) states, \u0026ldquo;This enforcement orientation is reflected in the emphasis placed on the criminal justice provisions (which are obligatory for states ratifying the Trafficking Protocol) as opposed to the relatively weak language on the rights and assistance needs of trafficking victims (where the relevant articles are optional)\u0026rdquo; (p. 83).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See Finckenauer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) for an excellent review of definitions of organized crime, and the distinction between organized crime, criminal organizations, and crime that is organized.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e For a brief description and comparison of the Shelley (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and Williams (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) typologies, see Lee (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e: 89\u0026ndash;90).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e It is important to note that not all the cases in the database have defendants that are charged under 18 USC Chap.\u0026nbsp;77 on Peonge, Slavery, and Trafficking in Persons. All of the cases are human trafficking cases, but not all of the cases were necessarily prosecuted as human trafficking cases.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e All cases are coded by two people, an initial coder and a reviewer. Discrepancies are discussed and resolved to ensure reliability and accuracy of the data.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Minor sex trafficking was defined as any sex trafficking case that involved at least one minor victim, even if the case also involved adult victims.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e 163 cases (7%) do not have enough information to make an organization determination.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The standard deviations are very large across all averages, which means that there is significant variability in the number of co-defendants prosecuted within each organized crime group type.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e 55 cases did not have adequate information to infer a group\u0026rsquo;s scope.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Family, Family/Friends, Friends, Race/Ethnicity, Accomplices,\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cimg 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k6Cu8RyEa8cdd6zbMC/5dnZ1NcS/lcuWVu5r7kwI8z0ze8z3mJkNfJ0J2z4zC9jdZmnDbF3b7Z9ZIdRZszPF7Kxz2vFtvxm37Xj/3aMtu+PYtq/tbzhmZmN9t3P9bueORjcs3Y+wtJnTe40yg3t2iKe4zKzcZ53ru2vNKUxwb2HrxrcbptnRn04+0nE0XNcxI127O+O5G5f2LPsRv+5x4tA9rj/PtJn1EG5p1va5Tvf5o/ssup/2vLs4r+2f2fD0ts6eOYW/zapvH+GdHS1O3efRf030X7f/eYlL/zNtH8+ilSNp0La7r+3tt/PRTWMfz92nu63Fq3tP3/ufUf9H3BryTstbPr7b1kU6tPT2X/q7RjtnpHwrDP1p0fJufzxamCEN27Vtd+1uerWwjyXOto32zMb7GYyG+3WP78a1MVJcuvjdn/7dMiaO3fD7tDiMVhZGilujW75cp6WPT39YMdL29773vbN++7R07z/Ouf1pJMzo5rHuR9i64e1HHhqpjhAP29wTs0uDhmsJXwu3/y09uow13461rnacc7rpNdJ9Q5hfGReBPN6oCMLko/JWoY5Et9LtFzeTDZGrUhfWbl5p24WxX3hqTFoDOsy0BrE18I22XSMYQpgz6ghlhijs0rb7DGNbNEh1dQjDzKSuYjFWRpscEcYffmjNFeW9731v2Wqrrer3Qaa9ftvKAN28Yghypmiu3w11Nx9X8TMUufHGG9ffw0xbQq0t1dV47nOfW/+P18TNEKY7zdWgu9wcuksNjrdveghheBhIgRwmDz6ku+22W/XtXWyxxUZd6aPryzeSX99k0pZx44vXfBjBl675FBLK4sbXfcMNN5zlIzvsvLznY3/sscfO8pvUAWh++sPQwQlhEFh99dXrf77DzUigTL3vfe+r35W15vc7TAxSXR3CUNOzJIf5lOaSwBdtNN+z7pBd+0z10J1hUGHuhonLBTcKrhbi0rbbNl3cdsRDfMS1G3dpMTufyRDC/8KPuOsf7+O37cPuXtE+cbMIYd5YwJ+ZhSiEEEIIIYQwk7hYhBBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4LzJhJ73sIQ8nNN99cfv7zn5err766t2X6cJ/73KcoorfffntvS+jn3ve+d1lggQXKbbfd1tsSJooFF1ywLLTQQjU/3nXXXb2tYRjxHO91r3vVZxkZEIaRRz7ykeUZz3hGecADHtDbMr5EIIeh54orrijvete7yvXXX1+WXnrpcuedd/b2DDd33HFH+dnPflYWXXTR8pSnPGXaxGs80cDrHGnkV1xxxd7WMBEQxzqhf/jDH8rTnva08qAHPSgieUjxLH/961/XOpPAaB3xEIYB9f5f/vKX+n3//fcvK6+8cv0+3kQgh6HnV7/6VTniiCPK6173urLKKqv0tg4/LOP77bdfWWaZZcpGG23U2xr6Oeyww8q///3vssMOO/S2hIniu9/9bjnjjDPKVlttVZZccsne1jCMfPnLXy6XXXZZ2X777SfMAhfCRKHdP/LII8trXvOa8uxnP7u3dXyJD3KYFrC2Tkc3BCL51ltv7f0KIyF9pFOYeJSx//znP7EcTwO4JCk3sZGFYUSbP9FudRHIIYQQQgghdIhADiHMN9x4443lJz/5SfnWt75Vvv3tb5ff//738e0OIYTwP0QghxDmC772ta+V1772teWjH/1oOfPMM8sHPvCB8sEPfrBcddVVvSNCCCGE/xKBHEKY9lh9wWznG264oXzsYx8rn/zkJ8uWW25Z/WnjgxlCCKGfCOQQwrSHQG6THf/617/W/+uuu275yEc+Uh796EfX39dee21dMu6nP/1p+fOf/1yFs0kgv/3tb8svfvGLcumll5bLL7+8Hmcf9wzH+3/LLbfU4yzLZ7/PJZdcUj/u6zos1dw7fP72t7/VZbbsd+1f/vKX9fOb3/ymXHfddXWbfQQ8uIa4/4UXXliPcz+YLOc6ZnRzFWlxcGy7xsUXX1y3d8Pbzv3Tn/5Uw+NY901nIYQQ/suCHzTGGMIQo/H/8Y9/XJ761KdOq6WnzNK1rNZDH/rQulZpGJkLLrigCtAXvOAFvS3/i3VfTz311CpMf/SjH5X73ve+5fGPf3x5zGMeU180QnTuuuuu5Xe/+10Vi4ceemhdU3uJJZYo++67bxXSRCk3DcucPetZzyqnnHJKXSKLMF111VXL3nvvXd7//veXZz7zmXUbC/X5559fXvGKV5STTjqpXocA/dznPlfX8Pz85z9fhbjzzj777Crcv/nNb5bFFlusvOc976nnipOwfvjDHy5f//rX63J2xx57bHn4wx9el/8jut/97neXr371q1XwO9/SgK4rzH/84x9rmMVfOu2+++7lfve7X10W6fvf/34Nr7CcddZZ5Rvf+EZ5+tOfXhZffPFeqv0v0se6485/8IMf3NsahhH5XHl4/vOfX/NYCMOEvKtzr85Sj08EsSCHEKY9hO5b3vKW8rjHPa6+6IJd4L3vfW+12MI62jfddFMVkFwwrAt7yCGHlEUWWaS+pIVofcMb3lDe9ra3VWstKzOR7GUZXprh+Cc+8YlVuOqkEcle8PKkJz2pXoNAduw222xTxe7znve88qY3vamGwTnEOJ9oa3kTvsK53HLLVev2F7/4xXL66aeXD33oQ2WnnXaqQp64xw9+8IO6aL4XPrAMC8see+xRNt988/ryB6JZXHWwdCCFgZhn1T7ooINqvD7+8Y/XNaT//ve/lxNPPHGWdTqEEOZnIpBDCPMFG2ywQRWhFpa///3vX0XnUUcdVa655ppqjXjCE55QLWmsrSussEIVnSy0XmNt/d/mIkF4ErSswbb/8Ic/rJZb7hX9byRjSV544YXrW/6cu91229V7vPjFLy6vfvWrazi4OjiOeF1//fXrNqMHthO/LL+svkSx63sZDhH9r3/9q7pIrLfeelWUG23wRqnnPOc5s9aF9p8gXmmllWpYhc29WKKvvPLKWUKbEHdNrhncOUIIYX4nAjmEMO0hJv/5z39WsdgsrOBTzE+XcCSMG23I2XYCmcWVLy+BuvPOO1dLbcN5tvvfFcfw2z6WZy4XXIFYkQ1vjwX35ofsGv0ID5FL+HIxOffcc+v3seA4abLQQgvV39xM2vcQQggRyCGE+QDikatBs+hycfCdqH3Uox5V3SBYklluiVruBo7j2+Y4gpl1ltBlsSUmHUdY2s7PmC8c4UnUNnwnXvkXsx5zZeAfzOe5S/85DfcQPmLWdViVhZN1m7jnB0ysc+XgOsKfGO0aI13XfxbpBz7wgTUs4F7imuJrXwghzO9EIIfQgzgycYmQ4h+6xRZb1CF5gmQ6YkieNVVc+eea1GUS1nSEcDQRbrfddivHHXdcOfjgg6tAfMlLXlJ9fbk8sMZyu/ACERP5uEAQwMQpv1w+xX43uCKwLDeXBCKT64Jt/hO0trFc82s+7bTTZrlSPOIRj6jnyHPcILpuDc5nNXZf1yHIidpPf/rT1U3jE5/4RJ2Uxw+aO8Vzn/vc6nZBPJs4COe2cDSayBYebhxcTlxPujiPm8laa61V/akHke985ztlzz33nFU2rWfNJSRMD7gLHXnkkXWEhb+/yadf+MIXenvHH+XdBFl+/bvsskt1t1I+Q2hEIIcwExXjV77ylfKOd7yjWg/f/OY319n8Ji01K9t04uijjy7bbrtttRpusskm5ZGPfGSdSDZdBfILX/jC8va3v71aR03MY+0lODXEeP3rX19FLCHNMmsiHTcM6fOQhzyk7idaCUyw7BKcG220UZ3o5jwTAf1mRea2QdiyLhO/L3rRi6pbhby111571ZUDYBu/49VXX73eF+6x2mqrVf9gApu124RB1m6dGr7S8ia/YfcGUbvhhhtWIU0A/+Mf/6jhJ+qFE0SxY4hm13rrW99aJ/wJA6Fu9YsWrkHDszKBkpV8s802q5MYrbrR0iwMN5ZIfN/73lcFMn955c0oy8knn9w7YvxRvnR4dVy9OEiZUy5CmMXMij6Eoeayyy6b8e53v3vG+eef39sy98wUQjM23XTTGcsvv/yML37xi3XbNddcM2OmiJwxs6KeMVNAzJgpfOpnppieMVPEzLj11lvrf9vs7x5jn49j55WZgmzGbrvtNuOoo47qbRkf/vjHP87YcsstZ8wUxTNmNg5120wRNWNm52DGRRddVH+jxcP/u+66q27zv8W7u60bb/9H2t5/rfHigAMOmDFT0PZ+jYx7ej7tubUwdnFM29/oxqE/7N3tnvNI39tv925p0L1Gf76C/8LRTWP4fcstt8zKa377j3aNdk777dOu0T2mYd/cPJezzjprxnbbbTdjZkeqt2XikTdniuIZMwXNjG9961t127XXXjtjpqCacfbZZ9ff4iBePt349G9D297So/u7PYO2zXnSuPvbcb77dJ+1345rv33a8+2GqXv9tq/dZzL5whe+MGNmB2nGzA5cb8vU8bWvfW3GUkstNeONb3xjrXfx5S9/uT5jjJRWLW19Wtp10985Ld1HQ10/U5DPePGLXzzjuuuuq9u69+o+k+61u+Fo5bVbfttxbV/3mr7355Puce2Y7nX8btje7u97F8e2PCZs7Zrtum2/37534+d7q18avjuu3adds/++U8HMjn1tn3/4wx/2tow/C/jT08ohDCWW3WJh8hphw83zAqvbu971rrps1ktf+tI65Dazwq4WObAkm2DFcsWiZ5jeEP3MiqK+nc2yXix6huitPMByZ31mVol11lmnXmNuMfTO7YHFcGbD0dt6z+EywnWE1UTY+MWKV0OVYAKYtXHFjf+tIe2HPexhdS1eL6aQLqywr3zlK6t/rfSx5i6Lpvgb+p/Z2ahWadfiVsA6w3rJnaO9nGM88FY8llZLpoWJhTsGq55hcCt5TAbyzNZbb11XC5GvLHcn/8hP3EKM/HjJycyGvx4vv84UA2Wrrbaq9QL4mPMbZ6lnOTzmmGNqObDOtDrDknfOU4dYEUQ8udmwvtv+8pe/vFqslXl5jcXe/1e96lXVAm/kxXnK6QknnFB/G7VwD6ubWMtc+CwZyI3FSIK1tsWhXfPJT35yXZZPWCcDywey0nI7EoapRL1i8qt600gBn/6WDtLK80EbEbGkolVX1GEzBVwdGZG2XKGsd64el+bSV95gnR7Jt1497g2b6qeZgrxe25KP6kBp4hz5w6o2XECkmTrRCI58aX6Aib+euW0bb7xxbRNYwuVRdSa3PXExAmUUx/nC+73vfa+OThplsgzj4YcfXi3a7ivM6tb2Yh95y4iPc9XL8pz2QR7TXjnPcfIUtzHlRJhsU1cLk3vLZ0aWuK6op+Vra5obVdN2ua+8bVTrsY99bDnvvPNqHS6OlqC0Nrv7Gx2TJlOJvCvNjNqJw0QQF4sQZqLy0HiqEFUUGlcVZvPh1KiqeDVyM3vQteFbe+21ayWj4VRBWRfXcB3fNi4a/Ex9HzS4AvBZVRGKq4lnRIbGAQQt/z9xU+ET+vbx2/VRcWuM+Grz2xNPjdi3vvWtOkQvfd75zndWNwP7pI/JX3x6uSx0/W1DmBPKprIlvxLJGniNf/PTJjKIS408lwtD9EQpocH1xXf50n7CnvsJIcXvui3tp1w7lxBxbXnbxEdCgUhxjzvuuKPme/vla+FSD+gUenkMVxzXcl/3FA4iRj3S1sV2Xf7jjlEWNPLqkWWXXXbWPeZHpKv0UjcQyDrw6g8Ql54zn3vC2bHEqnW9iU95wjaYWOsZqM88S0s6EolENJEofX18HwnPlQHA8yMenasuV/cTvPKQfLPpppvWPOlYE2XVf/yZzznnnLquOVcgAlM4tSnNhc1zlifkXSJce8E4IT9wM9FeCLO8rvPX8pZw6fTpKHz2s5+tHSmdBEtPqm8hnwmb+tY2bw+VLgwY0omxRh63Ik57uZZOhuP4YTtOvPj1axNaB4Ag1tHUYdQOCtfsXiY0nYhADmEmBK6KiTBWCajgWCRVSBrTZoHyUaHx3bRNj1pFqQF2DR/HqABZBlheBxHWAJUgK7lGQKN04IEH1oZIpa2hYelSwXrbmgqaACasWYbFVzqxgkCj5EN8q4hV/ipS12HFYcWwzT2JkhDmBqMOrLPKHtHBR5wvN8sf3/KXvexlteGXB1mTCFEdPPnPh0WNSCVKlWeiRTm1T97027nEE6sk4WCkyPrVRijkaSKCMHBd9zVfgQWvXct/uE6rC9p3QkPHUlkgTvy3z3lEIWuczihhND+iM6JTLj2li7c/Sl+dk/YcpRULKGFs3oS0ko46Kl1aPiA6nWvEwTGf+cxnqoXVh6geCXlBve4aRsiIY3WaUROC0TWFQz7xnfXdvTxfwthbMuVP+3zWXHPNGg/5RVgcx1Lu2u7RzYP+uzfxzkK7xhpr1N8tjm2kThrJl9KAP75j5GmCl7WbyNYJtKyk67iuPKgTKS0I+pYvpaHX12sDdNTU6TqFLMnKgTAS+uLumfhPtAvv/EAEcgg9WHg0thpek6pUSiq8rhVY5eU4lgA9dUOpLFqG8whAFYfKxaQq5/ZX3oOCSpKV10oA4qpxZ3VRyaos7RcnsIwRu+LetqlciWYVpgZeJa6SZm1gldY5MCznHB9Dgipn1gqNQghzg0ae9VceIjrADcIqHESH/MgKrAz6EJzKIlFCLBBHRJGVO4gAFkU4tv2Xh4kQ1kCiiIiA6xsql/ebG4c8TfQoG+7T7tulbZPfhZXlj7gTfucLmyFzrw7n8mHb/CI8RkLHRn3E1c2Ik46EESvpJF2IY9Z7o1asqY2R0l1+MBJGnOr0u4b62oc7R7NOj0T3euo4eUGeaPeUB4wCaCfUk37rOHG3UfcTse35OpdQ9huEddvW8ke7n+PFmaHCi4f89oFjuAGyPgsTlAnXcQxDhbzFRUhdbWRCvpX32r1dQ0dE2rR72ud4eb918ITPNcVZeBk0iGaWbJZozC/5NAI5hJmoRA1PaUwN9amkWatYglV6rWFsqHxVkvy9HN9tnIlivf/WkA8aKj7rAqsYWYRZiDX2MGTXKtD+OPvdhAUco2JVUbcKl2BmxWB912jYrrI1PMlq3fV1DmEsKH+GuFl/jdYYftf4G0YeywozGnPzFFgjWYYJ35ZfW0Mvb/vIz/IrYdCOGSvtWv3X9l89YvlA9ybQ2/1Y/1i3+ZHOr9ZjcJ/QOdcRYbVVdxJ3OuvST5pKO/WV0YJWX3WRHwhIz8/x0tYoQBORBO2+++5bV2vpnxfiHu15dZEP1HnqdOFxXcep89VnDc/XM1TvE/Hq0XlB/iNiuU/43s2DLV7dOhi2aYuElXuENNBxHAstzowbXSEN9XrLo9KLywrxr/0QlvmBCOQQZsIKynrBugCVjUqDtZj/GNGIJh412I4xxMUP8fjjj68VE1TIrLIa8S996Ut12yBhCNDEFK4UYBkRFxi641ahYeITBxW+OBtC5JsHQviKK66ogsMwnPNVqIaRW2UKFamK3oQufnPWsm3XDWEsyK9cnQxza7AJIWVTvjOSgyZs+xvulm+33377Kq5ZkuXtZg1mlZN3lX8WNGVdZ86Ih20gqJp4aHTFlGvZz/oHnWxiqglxgob/PRcKfpzEjP1QvxB8rHaGtHXU5zekkXqBgPVs4BlLt+4bK3UgiFCdbBZ59W1X2DJaqG/VQ54pobnjjjvOqouMKpgM5yO94Tj5QH7yH67X8tFll11WrbFcbDwrYbXf6Jg5K0YFhFX+kx+5AXm2fJUd27CtG1a4h99tn+N1ECw9ydfa9drxjpHPuDe0+lNdLN3Uw+pwPtNcN9ThfI1b/h2pXAhv+69udh+TrKGzIi103PyXRtoELoiOkc/7rzddiUAOYSatwTrssMPqGpx8jFUCVpEgAlVEGlMNJ0uHYVGViokRfMrM9rXdMXrxfCRdY3ZDeVOFileD/qlPfarOpm4+cixz/Iv5ovlvqE/ciAqNAJGhsuSaIV34tPGxJpZV2qx5KtfWMDjnggsuqBU1UeBaZojPjyIgzDvyq47pAQccUMsm30r5lc8qiyKIBXlQ2WsNPaFqOxcpIrsNgescsgASTFw2lFUWPx048O0klr2UxNsPWc2UdYKNZc512yoCUFaMJFnhwGgMFyNiQjlQ/tUJ3DtsE27uV20lApO89tlnn+rLalSnX4jPD0hbFlrPykoNnjEBzIpM4Bo5ULd6vizA73nPe2p9rK4h1ohqq1R46RFhKk09Z8/KM2vGjX64e7mP52kyJ3Ftm/O5zrWXh6gjWYtd00gEtxj5hk+6cMhbnidRyh1BPiJY27NU/6kHjdjJn/IF4amzJG+4hn3yiv1EeRuVsxqH+HNv0HlTBxPs0kUd7Fw+8ubMqI/ladfUWdChFB/5X3ykDVxP2gm3cOl0mJzHJVDaMv4YQRUX4XGs68m/rq/+bnX8dCfLvIWhZzyWeVOZqSRVZj4qbC4CPsSzipgPnIqLJYEYVPGq3AlB2wxFqUTRtuv181OcFzTAE7HMm0ZDODUM4sTiLYx824RblaCSFWdxkBasauIrjTQQzaLBB8/1DLsJr21EgOtoBNzHPVgq/Lad9YboGS+yzNvkQVBM9jJv3fyqcVbOWIXltdaxtd0x8hgh4Rh51+gOlGP5l48x5EF5XL6VJ9tIkU6xa8j77qdesM9EJdttc54y45rNEqfOIHJ0IJslWths04FUTpQx4REuZUSeVdbc33ntmpNlnRukZd6khbRSt0hn6SC9pL3nL91slzbSijVZvdSeuTT0rKSz755T/zPqh9XY83d9uJ7noo6DZ+NcVt2Wn+xzH9ud5xxhFHb39ml5UX3arNnuww2j5QO0vCCcPn6LnzC7LtxPvWo0Qp51T22PPOVYZaC5RxixFC7C1z3dS15scVRmpFtLT/Fraex6jhMeYXYt5UVe95EGwuQY4r/dayqRdyd6mbcI5DD0jIdAHkQmSiBPN4ZJIGuAhJV40iiqfokCjZ0GbdCZCoEcJoZBEsghzC2TIZDjYhFCCJOEoU4vvTAkb4idNYfY5D4QQghhcIhADiGESYLV1Qx1Q5Vtaa/llltuWo18hBDCdCACOYQQJgmCmI+hl1ZY9uuiiy6q2+PpFkIIg0UEcgghTBKEsAk0ZsZbhsryZXySTSwKIYQwOEQghxDCJEEI8zvmamFSqaWXLGEVC3IIIQwWEcghhDBJEMeWTbIUlNe3crWwBi/XixBCCINDBHIIIUwSFum31io3C3hJy3rrrTfrzV4hhBAGgwjkEEKYJCyw721hVq3wggNvdPPGRa9yDSGEMDhEIIdpw3Sc6CROmcA1Z4YljbwRy9uvvNGqvTGNRXk83yw4kSQ/Th/as8zzDMPIZOTdvEkvDD3enX/wwQeXddZZp7zwhS+sr8IcdhR8rybdZ599yjLLLFPe/OY3T4t4jTdeh3rggQdWn96ddtqptzVMBF5Be/rpp5fTTjutvO1tb6v5srmKhOHCszz66KPLpZdeWnbcccdZb3UMYRhQ71988cX1bZCbbbZZWWWVVXp7xpcI5DD0eDvZlltuWc4555zelhBCCCFMZ7ioHXXUUeXpT396b8v4EheLEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdssxbGHqsg/zJT36yroH8nOc8p9x22229PcOLdZBvvvnmur7z0ksvXTbeeOOsgzwCCy20UDn88MPLv//97/ra5jBxeMnJt7/97frZfPPNa77MOsjDiWd5wgknlMsvv7y8/e1vry+uma5SwAt5Dj300Prf+t133nlnb08YDW3oQQcdVB7zmMeUTTfddODaVOsg//KXvyzf/OY36zsCsg5yCKPwq1/9qnzmM58pr33ta6tAni4QyB/96EfLE57whPKGN7yhtzX0014Usttuu/W2hInCWuOnnHJKeec731kFchhejj322HLJJZeU97znPVUgT2e8cIlA3mGHHXpbwuwgiPfcc8+y1FJLVQE6iMi7jCOvf/3ry7Of/eze1vElLhZhWqCfNx37enfddVf9hNHx3JNGk0PSevrQnuXc1JtGDHRGb7rppiqihqXOnex6VNowcBjZ8t9bUX33fxgs2C1vzC7N7BOfW265ZVac5I8W34lOb2Gc6PwXgRxCCCGE2fLXv/61fOELX6hD73vttVf51Kc+Vf74xz/29oYuX/7yl8vHPvaxcthhh5WPfOQjZd99963p9f73v7+6BkwHrr/++nLAAQdUS7PXz+Oqq66q7o4suzpRw04EcgghhBBGhaXufe97XznkkEPKi170orLccsuVn/zkJ+VPf/pT74jQ5Qc/+EH5y1/+UpZddtnypS99qYpiLkk//vGPq4icDiy66KLluuuuK8ccc0z57Gc/W/7whz/UOF5xxRXVnWU6uO1EIIcQQghhVEwQvvDCC8v97ne/8tjHPra8+tWvrr7LD3zgA8v3v//96pv+ne98p/7/0Y9+VK6++uo6mbNt/8c//lFuv/32csEFF9Tf5513Xv3PKu2/eSTgV0pMGqrnkmCf6/z0pz+t1zzzzDNnne/7b3/724F083jFK15Rdt5557LyyivXicQPfvCDy/rrr1/nSRCWBPQPf/jDGs+f//znNQ0vvfTSWWmm88FNg9g899xzy/nnn1/OPvvs+ntQWHDBBcujH/3o8qhHPapO9jz++ONrXMVv8cUXr/vBkiwON9xwQ/195ZVXltNPP70+T+hIfPe7363PXT4Rf89XfH/xi1/UfDNVRCCHEEIIYVSsGrD88suXP//5z2XHHXesQo4VmaAhfr71rW+Vvffeu4qfz3/+8+Waa64pH/jAB6rF1EoDXA34Lh999NHlqKOOKv/85z+rEHK8CdZ77LFHPYdQIoYJcpNv3acJKML4jDPOqO4LLJZ+2z6ZvsVjZZ111qnW44YwitNLX/rSssIKK5RPf/rT5ROf+ET11/3KV75SxTGRvP/++9dVmaTJWWedVdPigx/8YBWTv/vd72qaDRJE8EorrVSWXHLJ6mYhvAsvvPDdnsmpp55aOwbih5/97Ge1c/W5z32upgm3Hb91rFik99tvv/psf//739cOFX/mqSICOYQQQgijQgi9973vLWuuuWYVvb4TeYSRZeKIPktTspJutdVW5WEPe1i1jr785S+vQvqiiy6qommRRRYpiy22WHnyk59c97FGP/7xj6/i7+STTy73uc996m+Ww6997Wt1hYINNtigbLLJJnUZz1122aU8/OEPr8P3VldYY4016n2HiYc85CHlZS97Wfnb3/5WLeZEslWKWJlZ6KWhtCIkWWJZkp/1rGeVxz3ucTX9B4U2SY5bxZZbblmfoRVu+CY367H9xK6w68zAqIPl41jJWZ51uohg1uj73//+9cMqvdpqq9XVKabSVSMCOYQQQgiz5YlPfGKdZGZSFlFKwLIgP+hBD6r7bfN5+tOfXv8TfkQ0YbThhhuWhz70oVUwsYbaznrI2khkv+QlL6mWRsLYGs2EE5FlmTFC8eKLL65CkWAkvK2aQGg6l7/rsEEE6yiYwKejoGMgHiY9spzrSBDD0gLWrP7qV79a4zsoeMaEPLcKfunPe97zqoWfFVl8wHWG2H3xi19cLeOem3MIfuexoj/jGc+o8bW9XZOLxUknnVSv08T2VBCBHEIIIYRRMdxNzBGlBB1rLsHqMxKEMEsgazDXiuZ/avsjHvGIssUWW1TrMT9jAmjttdeuFkR+xY5nZSSWiGjuGFZLGMZVEcTXB+LT0DFgHRU/4hLEI9HMPUNHZMUVV5x1LoszKy2r8yAhTjosOi6s/Z7n3//+91mdFq43jjGZk2WZ1RhPfepTyzLLLFP9r7loNEEtvo63zciBdJrKZfEikEMIIYQwKgSu4XMvLvKfpfeZz3xmFTowkYrYY/0D4UzYOIagZv00BN/2E8VHHnlkXfmAqHrkIx9ZhSFfZ0KYaORycNxxx1Vxbq1d7gcgyHyaeBxkWISFVfpxJegiDQjJZiGVZr7rQLC2Q7xbPPlrWzFiUPC8rcjBdxzPf/7zy+qrr17DLF6eo4md3nDqbXys4XyKxUdcHe+NnCb12WbEoe0jjFmcCezWuZoKFvwgD/AQhphrr722+sWprAdpCOqeomI1PKmyNAwVRkalq1J9wQte0NsSJgoix0x61i8CJgwvRC6LJKHShvJHg2Ah3JQz/qLrrrtuFT0svYSwiXQswiyJ6iv5hK+w4XVD7/xIWYbt45/Moshi/KQnPakKR8dZ8WGJJZao/sl8VFmpiS+ika/xU57ylCqmhUHecy4r9Vj43ve+Vy2Tz33uc3tbJh71t5UZ+Gfz02UdFmeIg7h5SyoXFeLfs5DGjpFGkI6s8KyyzuGa0K4xkXim2h7prJMzEoQr6764edaeLZcYv9UPnjHxq01mIZb+OkLEM/cK+c4z1gFyvnRwDc9bR4nFWZsu/q0T0UV6sUhz6ZFfJoK8ajoMPfyc+LR51fRkVoATjR61YU2V6Bvf+Mbe1tCPhelZK0wcChOLpZdMptpmm21qQxiGly9+8YtVwFlhgNCdznixCWG200479baE2cE6rO0heLl2DCLyrheSbLTRRnnVdAjjid6v4SHiWk91NFg92nGWoJlbDCmacMIS4Fpmc9944429vVMD4S1OrD5z8u9inf/Nb34zLkvtSAPDZlO5ruVEIA2t58oSIm1nhzwgPeWl+ck2Ia6Gm6WRvMQaZnid9ZAlzXq2trO6GUpmfWrD8V3kHftN9JLuzmHRlk/nFWHhC9n/VjjblZGRwnFPkR7SwvJe/deXHmMpI66hTAl7CGH8iUAO8x2G6azNafF1M7G//vWv9/bcHY0U3znH8btjcZlbWC3c48QTT6zDUXrlU73Yu87BwQcfXOM0J8TdTOPmZ3ZPsK6nNVCn0qdsomBV9QreOU0kIuys88ktxJDj/AIx5/nz6NNBZKFi/THr3QsTvJbXkCn/RWvAWutW2elHmbQGrnOln/SU7tZQnVeIbGuxeoZdhNOksYno0Am7mfrWBybEu/C7nF2nvYsXTnzoQx/q/QohjCcRyGG+w9CMyQN8Vt/1rnfV5YugEW8fsLJq1E0Yefe731194FiULDvEEkrkaET5QVmGiEXLuSzGGlb/YcF4vlz8y/hT8b+aSvgJ8g3j99b17erGv6UBvzDhbhNkGtLBIv7SoUFEE9QabZZAFkJD8tb6BFcR12rXni5IQz6W/Oz40jVGSk9p39K/C8Eo7fjSSztpyW/SMlpEo7wof8m7fEeHLQ2JXeVN57TlOysi8DHkQ8gHVrpIQz6Lbci/Pw2dy3eRxd41pZsyxTdTmvGbZAmWVtKSZZp4NnKjnLLasjZbikqagh+rIVphc4xzwLpt+SlhdT1lXJnXCTICoB5wrOem08eyrb5gFRZWo07qANdUBtrzsy4syy8fWj6XLMDC5zm7rjTggwm/lTP3Mjrhfu7hP5Et3vyDQwjjTwRymO+waLlGjyVKA8RvWWPGEnXooYeWT33qU9W6quEkeA455JBq9fUWJMfzdyawiT/HapidZ1iYRcvbjgylsxq3RdM1mGj/pxJhIC6Eq0GUSQ/xEF8zzIkJDXW/pVN8vQVJg2+tSoLYJBKWL9Y4aUeksMxr9L/xjW9UMdJNh+mGuPXHz7qu0tNH3iKM2mSVbppKe8fobBFCXtkqLxm9IOZYWPlQEoPEsbzX/0yGAYJYZ7QJRp1Gb2cTf3GXXvKQsiad5CVvGWvl0n95z2Qu1maCVr7TifNduZP+jlVOpRsLrXsRoPIh0axzIn+7Z0N5ld+JYOmvA0iQtvV3vQXMd89FmFiVm9XZc3UPr891LOu3/K9OUaaUD8JYfdE61c4jbF2PsD722GOraJeHhLu5d7iHsBHRhLK0c+999923po8yGEKYGCKQw3wH0csirMG23qSGyexalmJWLv9Ztlg7HWfW8Mc//vEqTDSuGjEWJxMYCEBL2xCcGm8WIULajGW/NZSOH3SE0Wxz8fd5znOeU9OpvwEmQDTyxJrF/VlOWe3aULRrmFDIGmh5J/+JmCaQ5ye8QaylpzzFYkgM9kMIGW5fa6216jnymfwjT7FWElet88WibOb3MMIq/LSnPa1aXHUclSWWY3mMILYKAuux7fxyWYvNoO+WS2LYfqM5xLT0YEVlVZUPdSiIYX7eyq/reynDxhtvXMu4+0pHnWSfhg6H8izPEp7KrvC4PrFquTHPQD6W/4VZWXANa/p6tsq98i+/O1/4fV7xilfUZ+saVjTw+1WvelWtO8TFGrfKiREXnQYC2j6dJZbyV77ylfWlEc4VV+EkvrlshRAmjgjkMN/B2kT0Wp/RYuwsV6w4rEqf//zn63/WGlYqx3l1qjcBsegRLc3twPCrxkojaBs0oizHBCSRMxETfMYbFiuNOh9r8WcdZkUzDNzvDuJ9+wSdBh0aeGlCSBBAhI4F4DXyfK8NPRMN09Vy3A+hJQ+wgvKvlZ4+fK9ZIaVPF1ZFIqgNqctL0lTnzSoRRJ9OiE4YCylRxGVnGNFB0vEkYFlrdQYaypLfLMrKlnQUVyK4lUtpKK2k4aqrrjrLwk50c4fwXweND7Pv7kcUy5eEJ8uza7IwE6VdNw7pL82VWend8qtrKMM6Kp6BN8J94AMfqPlf2fDfEmXqFJZj1l7XaR1L97ffvdQnjhd+HQGdJeFyvPqjlTX73bN1ImDZL3FVV7mX82I9DmFiiUAO8x18O4lAIs4wKkuphnvHHXcs2223XV0K6HWve1210pjMpqHSKDmuNZasSiymrqExdR3HGE61TQPP2uR4x2k4fWcZctxUomEm4FnK/DfhSZgs3SX+O+ywQ9l6662rlU68fISfWCOmpRW/TqKYWOZbTJAYvmb9PProo+t3Iojg0/nQmPu4j3SYbnjG4uajg2TInZVw++23n5WmrJPyTssDBI+0In48E6LaiAOBRDStssoqVRARxKyOBBgBOMwQvwSovNN8/1v+grIkjWwjAll+W7mUhtY71SGT3+Q9AhTyoPLGCssaLz1ds10XrK9Equtbb7chPzpOWfAc7W9lVRkhkj0D+Z9lmEVf+bfP8VAuxInQlt+dLww6iO0YFmDuGcoG4d9GCJQL12tlw3/n6nyzIitTOleev3u6ZstH0sm5g4460Uid0QPhFicfZSCEQSUvCglDj0pWo0O4jeVFIXyL+SgaKjVEagiWBYu1hqXHfyLFd+JYRU7EsB5pBDVKjjd8q/FzPY0dUWwYmDXLNg2ihs6xziEMWIl8xmIFdK5GmQV2PF8UIr00sgTBZZddVq+/2mqrVVEmzj7CKj4EmwZNnJzH4k6kOVbYDIGzrLEaEwd8ZFnqHKdRhN8tfdzXc3L98cJzJBIMw08FBA2x5rmalEXkeFUqgdPSs+UpxxE3PgSxCWbS3vFGLeQbnTN5RhqzOEpjw/2ua7hdWk4VRhWEe15fFCKPEKc6XyyrkGb8cYld8fbbd2kj3brlsrnpSGtiW16UZl4u4dr8hNuLGeRtFmFlXNrDNpP8TAxsKAcmmxotcn35trlXKOPCq1wT38qAuDtHmRYuot392sRB++0TXsJbPBynHLRrcGFyH89UnJulWhykhfC6jrLJ/5gLB9ca+Ue6i6M8r2xKB8e1UayxMjcvCrmnuL7VNohk1nu+1TqHm222WY3zRDMVLwoZZnTa1O/y2mgvCplq5F0++XlRSAizgaU3LwqZf8mLQiaPYX1RCLcX1lj/WfJ1XuZ3JvtFIVza4H4EMr9xcxcmg7woZO7QAcyLQuJiEUIIYZrDys9KzOIccTw1sJJzPzFZkfWaRTeEQSYCOYQQwrSGvzN/cO49YWowbG84nCWZi0kIg04Ecpgv4CvMH1Al3aX5Eo6Ec+ybm3Ma9nthAH/DqYBvok/zoDK5x6c/Lg3hdTz4QvrteH7Qk4FVNFj4WhgGBfEfKd8I52h5YKR84znIN3OKH0unCX78X8P/I03lkZanPRPfbfeRbn7Lu6MhPyuPk5Wn+dt7ltx/5neUBfM5WJA9L/+tKNLmKYQwiEQgh/kCjatXJndfJ2uBf6+4HU3EqtQtLcW/uc0UN4v9wx/+cF2qanY41/VNdNAg8Pfj/zhZEOd77rlnXQ8WJjGecMIJ9ftIaLA++tGP1klMfPWsxmEZrZGmKIibCRIgSryAweSoe4JJgO5nUuAgYTKnF6d46UkTvJ69dbGtpzsSnnd7HXI7x+Qs+cakktlBvPHztWoB5L3JzDeDiImByq2VIvbZZ58qrM4999z6EhCCWPp4RiaAjTaBkf+xF9hYFeRLX/pSFdgTjbLjBSDcCeaEDtGcOk/DjM6JSc4mRJtgaULttttuOxQrcIT5lwjkMF+gIWWhtLyS2eb45je/Wdf1HW2CitnkXul6zDHHVKHkGlYaIHpV+I1+y2wTlWant9UNzLL1u+3zfyItWfz7CIYDDzywWjP5/xFpbRWAfsy4J+h1IuAcArDNMGeha9Y5AuWAAw6ov33Mou+uaEB8tHiKo087tovGsVlhrUTguG66DgIEl+XqLN3WBLG3B1pyy8oBI2FpOysxyDfSSt4getsSVw1x7aaJNPN8rGDQOiBWYJBv2nHdfOO6xDj8b2nOUj2d0LEjIC171/KZ+Or0WR1BXtfBk0dHQgfYmtTS1ooh8nRLQ/9bGkpPebKlcUvz/vR0TNvmnG7Zh/NtE1bHyQO2dZ+163fDqwNNxLdnOFlIk8nwBVbHrrvuunXZPuXDEoibbLLJrPXUJxp1sE8YG/KE9BqtvRgE1M0THb6sYhGGnrGsYsFCaQ1SjZCK2dJNLEosUSxKLJcEogKn8TKRx5uxWJjtW2ONNerv97znPVUY+W55JI030WMNVr51GmwvIiCIXc+kIP527m0lCvfTYG666ab15QfCoeEYCeJxXlexkCaEPIvZ2972thofIs1bv7wSl2hQwRAH7m/ZNatAaNAtwyRc0srxXtQAw8XWo2Utli58Oi0t5V6WoLL0lHWjpQ9L9Bve8IYqJo444oi6bBahKR3XXnvtehwhSLSvs846dckvIsE+L4uYGyZyFQvCTD4hkK0Nbf1d4liesd6uDpT/Ld9Y0suyd3vssUftVHnboHwibJYKtJ4xkeYa0oaF3/ORb1idLTXmhSCegbwjX9uvYyY/vP71r69rePOptbSZtCWg5SnPmAhjcVUWJmJm91SsYrH//vvXpeW89bK9RERnQ35hRdZx8XIQS+DZ73k0oSsvKn8szNJm5513rh1fjb8yaYjf0L88ZylFz8B5yrRrEdM6OwSdPG5JQWuAKydeHmSfcmJ1BIJdOOV7ZcbSbI7namHJPtfyZk7bjBAof8qZPCFvSU/5Rf6ZDDFnspw0UJcRrdNVCsgvDCP+q2u6HZUwMuoyI4M6MPJk60QOCsqHTrGRUuujW0JxIsg6yGHoIfbmtA6yRopg0XAqXI63Vq+lYjR+Kk8VpwZVY6Zx9GF5siyUIXYNHrFMTGrMNMwaO2ukckkgcohF9zKcyHrsugovkaURVvGw7GpcHStMLGMj4VgiV5jmdh1kVnLijjjTWIsr95C2RiuLTotrW2PX8D8BZn1S69CqFK2BKV5esiDNNKSEmXDtsssudZ1ZcfcSFcJMpSU9CTbHuJ81SIkL6UYQm6hDLNjH2uwZENeEN+En3eeGiVwHmZVPuhFE0kFcPTuClTWsNbbdfCMtdEyIfQJEerV8Q0CzDjufADaqIQ/oPLAoWwNZviLi7Pcs5A/3N1Qvr0kvHQLpR6xaQ1maatB0aKQp4U2Ijzf3dB3keUGnRJoZtTDSoBzKR8qUjkkTptKJ4FRu5EvPw3OR5tbplk+IamswE6dEs86H58KVilD0fHVulRtlXjl2rDT3HD0P5VkZ98yERae3re2rE+m5KQeeizLlGGXiU5/6VHUxcD3PSz1kv3MJZufJW/KZemOiEVbxVRbFRz0qL07Hj46Mek+5ms7xHK+PNJJmypL8wUVxpOOm6qNtUweoB9WJbU318SYW5DD0jMWCTKBoyDTq3Co0tCw9LLSscARlswQaHiW0iTprdrIM+6/h8p0o0atmNXZNjRqBRqDbZ1iceOJ/SKxsvvnmdZF8VmDWKtaM973vfbUBVhGxHo3EPbEg61kTBK95zWuq2wQLOoH+5je/uVooVTAaahXgWmutVeO29957l913372mpfVJxcFHeIl96bPeeutV4SXMfIaJOlY84sQ9Vaas415uQIDwa25rVRIUtksP/4kO4tOzsI1FnYWHeJgbJtKCrDK2XquGlYiRbp6lvONZE7O2NwuyZ09csSh6AxyLIZFGuBJ0a665ZvWZlb7SkRDSQfFMCKkNNtigdmg8G8/87W9/e72GfKKz5vkQ3SycwmB9V1Z5wpClVX4RHlZOox3jzVStg6wjIs9IU0KUIPZfXpWvWH6JUOkg/jp3mjYjHDq4Riv8drxyqzOlHiC6PQ8Wf2Vcx4ag1iHkZ87ibJTA85LeOoXyqHyuE+lZK1NeRy9t5AOjAPKC9WM9A/fy3Alwr18n9o3iKFOeo/vIL66rsZ8smluHOOowT1cpoCzxXfdf/ul3iQl3R52kQ26UUDuoE+n3IKE8MzTpsGpvRjMy3VPigxzmCzRYxA0rkEZTA8hyROC1XjKrEwHt04YcNWAqByJSL1XjR4zZ7nhDUKy7rD+GuP1mPSKEiSfXdqz7aLSbBaP1gCdq6EqYiXONAVHP8kdkaMA1hi2ePhoO4fMRPkPVwuU3CxexZdhX3In2Zt0iHv12nPsRDASvuOuQsNS5jnDoQPguLRzDYidNiULXaPdz3CDh+bGuefMhP20ChkuD+IqLirqlo/zQzTfixIrMqky4dfONvCffuB7rJmunfCNfEGytEXe8NNGB6eYb4RIGaea7NPTb9/Y8pgss46yd8orOlPRg2RdXsMS2dOp/Hj7yovkG7TlKS50WVjEjHdJUueACI6+6rutJQ89Bekpf9/EcdYJ0itUlzlP2dU4IXJ1ZHQj70PIBXItLhw6jsqEz38qFMOmku89kIk7KvI98PR0/0lb97iN/jHRMPv//afmhpZf2YaTjpvKj3AmjsE1kxy4COcwXaHgMO7Pe8Coy1Gl4W4NLPBJ/GjiijUAkoDWeRKWhJpZT1iANnGuw/rAwE9smwhF8GlTXYNFiqXKsbSylGkoNMTEEVkINbxOP4w0RKl7uT7SzRBILKj1WrxZXVjfijABxrDASAKwGKiJWQmnAGq6hETfibtVVV62WW24U4uk8lkwVF39dPsispkSJ9GLBFl/WOxUboeGaRB9BQsRIU2k+SBC18gkxxdLGEu63YXjPlfVXfmn5xrC6joNK23Esws7TaSCAfAgqnS155KCDDqrPn5CWP4kn4k9+5XLieXmW8o10ks/kJcd4vtJeHpJHCS3pSWi7puOmA/IFqzkR2vyMxVE+agJX+vrOvYXLgvT0kdbyq/Th4iC/6uxxEXGcZ2CuwFvf+taapm0pOcf777osyMqG68jjRjrkfWUBrud56vAYpZE33Fe+14B7RjqatrvWcsstVyd6soC5puuwMFul4/jjj58lqAcNeUuchE+doGxIF3ndM5C3be/HcfJwy4+to+g8311zLHnVcdKqdYymgm45FqdWXylv6rrZhU0HSTrJz87XEZbn5hb3kKfcU70pHCOl+0Tj+YmHfCFuwqOe90z7sd8+8Xee+k24J7tDOLfExSIMPWNxsRhGVB7z6mIxP5FXTU8eU+ViMR60pm4y/HuHAS4WOnljfdW0ibU60tx6dMp08nW2uZBwE2GNfuc731k7Ll24reg0G8kyF0KdxoLOSMFtiAvXrrvuWo0Us0PngduY8LL2zw3j9appacaFRztDnEIHWMdLHMVffT0SOhYmcBOG3MgYEbgGMFLMDToKlpo0b0N4CGaTp41ejRc6Pp6TUdHRXjVNlOu06qwyEjEI6MAzJvW3wwS9PKLDz53JHAz1iI7paOk1J+TdvGo6hBBCuIcQxhHH844RM6KQmDZKwqeecQJGh7gL9Ytj8Onm8gJijt8zgeRZ2G4EizhmHWZpb1ZVllaCmPCC6ziOtdnoiUmrk21tJ+aE29wMRgtuPxDWCy+8cJZoHgniUCfCRGSizugStzRWVYK3pSWrLNFpRMkokjia39H2M5wQp0YfTGA1Muh46cSKTYD7PpIldzzR4SDu26Q5H+ljFK0f7mlGbNpIopEaItpopXiZX6AD6yP8RlPMM5jq0ZQI5BBCCCHMFm4+BDA3ERZk/tzELIsm6yU3E1Y9638fffTR1cJs8qnzuF4RflbNIKoIXGKOK4tJlOY5WO3G+SYwElIsy8QSK6n/BBmBSWC5h2OnAnEXVtZvS2QSr9zRTIgmTAlYcTWJVDpYlpEPPGHvOK4V0kUcWZItt0dY87Un+qUna72lDE3kNgma5d61WJ0JX/+FAwS7zgUrOTwf95yMziCByz3IEozua0lFz8mzY00WZungeVv9hW++kT7P0CRl8bNP58JzlzZcmIhunSV5ZCqJQA4hhBDCbGEBtewjYUjIEITEEP9wQs9cB9ZgwpklkXWVaCZq+eoTflb9actyEZashEQTQUX0EZf8swlvFkb7WCYdaw4EIUl0ufarX/3qGqbJhj8tv1siF4QhMceS6z8/Zdbdlg4sxlaDEH4WUlZR6aez4Lf5HFZAEmcCmR+9e0hT/upteUfXZ2k174Ul3vFEMGsyVw3C2TZC3D2FYaKR/sLGIuw5C7M4ia8wiL90EBYfcWXt5p6lU2U9eJ0JYedC4/lzV3Fd7jssz1NJBHIIQ45K0YsSLFfHcmDJKxYWvfB+VN4sFny29fBZeSzHxkdsqjC5w4SlNpQ6TLACSUvWHg2DJeGkv3QeCXHkh8j6pREkLlhYNGrEgqHFkSAgLFUV/ouVPCwhSDx0MSRt20RMWlJGlBUCrguxZBm4sdxTWfUc5ZNhgxXY8Lm4EjUmJ8IkRxMQCUBuAfYT0XyPCUbwl2UtJqS4aBDarKpNDEo7YtBLU/j0srQSoCzHVhxxjPLFJUO9RlAJz2RDkBKolvnkC90mIbOk8oMl5oXZ/5YOlhMkhpvF1wRlk6QtD0joKvPys7hJB/E0EVVngwsGCzxxye/aPoh710Jssjmh6gVGXFispz5ZCJsJqs0vXF0mTuIt/vI6FxToRMkL4iYv+K1zYPKtJRS50bAwO4eP8kSU47khAjmEIUfDzVePVYU/l8rasJWKuh+Czj69emJND5+gmAqBbNJGq/BNCmE9GDY0UkSB2ey+W9pPGo+GzgAhbIhRI8cixprE+qKxbI1oPxpV1qPwXwz1y7PESReNs3zU8tV4QrR5Tp5fP2MtP85ndSWIhg352+Q6aU7MEUbSWZwIHfCJ5VvrBSv8dNvLe4hf9Q5LMjFHJBGNVgVxLdtYFj0/4luHU13mHrYrGyyv7meyn44QAT4Rz3l2KLeetbygDhVG9ShhL462WS9eJ0Aa+PA3tt825+sksZ6ysir/OgLSgCW6xVMHQKfA8eoE8bRN/UE02t6OdT37uTroSBPX0m2yEE5ha/7C4sbf2PMXf2LdZD+0Ok59b5u01E6JlxWOlC3l16pA6tKRjDyTSd6kF4YeFpw5vUnvnnL00UfXCl6lriJTIbH8qawm6p4qE8NNLCize5Meyw3/LmtWGoq0xJSPSldFpAJV6aiEDFlpnPzXyDhP5U0kG/7UOLEIseyobFnLXMfxfMNYRkzOUZFZ0oplwDG2CYfGjNXAcSxELAUaTxZT1g2+hkQ560pbGo8VxvCqxpPFhNWJb5rGh/VEvGaHzoG4TcSb9OaEBp1w1Slh/ZD+8oZ0tU9jIO19xMNv8dKYimtbyk1asrho2DSyfPLMimeJ8dH58Z9I0aCarDSWlQfGG2XAs5/MN+mNhLIhreUdYkq6EAbylXRpb7o0hMty6beJUFYgkBelpTzO75O1isgTnxNOOKHGkY+pPEWIs/IrG4Stj7yqE6RBb4JIHWSFBs+ccFMmfHe+cuTj+u6pQyW8syvTk4EyT+waylZ2x4J0UhfwNRUf6SHvEs46fMSR8u7DosjaCoJSWec2wb1CveAZEkLOU35YFNWt0sVQPXHkGbBaKz+u5RjWZ+XEc3LfkSYG9uN5SvP+1RXmFmkmjsIvHeRBbYDwS0MjR8SrMOrUtnTgHqEelt7EJNcRnQLxaCJX/ml1nevIW83I4Tshri2Q7nyOCcwm2KWZ9FG/eomT9L4nEL3aHvcSl9khTjp88rY6sJUl8W55oeUvHQJtjBEH4ff8+FcrP/KhtFSelWudpzYJciTcV1shr7jeRBCBHIaeyRDIKm6NraWJCL1WgWkcCT6V5XgzVoGsgVE5qjBU4Kw4KmyVEZcLM8abMJBGhJnwq1z8Fg8VqjfE8RFTORJyGgFig5gg+Ig217GcHtFAdPitIdPQEYYqvQ9/+MO1AQWx7JpELAFL3Gmo+MwRJqofwkbYNLYaC2Kb1UFlLz7u7ZzRmGqBLE5EE0EmP0g3cdYBMPFEGklDz0naizeRSSgJO8HgeI2M7X7La3wsNewaU4LYutGGZtuM9Yla2mh2DIpA9ryJYeJIx0qjSkgRLESDvGmo3tvvpJX6QbnQ0ZXndUqkt/zqY41kr1l3Hc9Lw0zgeJuYNG/liZDRwbGiA9FrOwGgM+jlId6UpzzodBpVkK8doxwRzgQaQYBhFMjSra2cAGkkreXtOeE8IkpZJgQJL2Ue6k9Ch0hU36mPpI+8z5e1PQ/r06vr1Lm+E6tjYbwEsrpS3SWMhCBBqH6SHn6Lo/0jCVRpJx72E8bC0zrHhCJjgHiJp2PkK3F3fcdLL+nh3uoLdUkLD7cKHUH3ZRy5p8yNQHaM8Aj7nPKBut7kPGVW/Iloz5zBQBmRjuJrmzpvdvX+ZAjkuFiEMAZUxK3CZoH1X8HUQLOMDCI6C/zc3vWud9WPZYman1g/GkiVk5crbLLJJrWSVQETfQQH4aoy5+dGUKiQiGiVOsscy7qGUkVOIBILKj1iwTaNMMtJs2ZrIFWmGkaVuvtrLIkPFaV7q/iJG5X1oMLiwRIk3d7ylrdUv0xx07khuKyL6uNFLRoGglo6G4b2MhZCs4kE57kedDakk2tLDw2F9NXxkPemenb3VCOdCCUNs/RQDuVTeVRaEb9cV3RAWOHkL/mIQNEAS3/CV+Ou89ttiOXbtgQX6xwRQsRYfUGetV9+lm89oyYu1QNGE9QPhA0/VascyOPKgWfmuQ47Lb9Cus1OxHRxXvfYfjHlN5HZjun+9t35/vvtu32Tjfu3sKAbphbO0cLV3e97oz9e3d/+d79397fvPsSxjutUrJffDduc6Ia94Xc3zXxv5XiqmXOMQgi1QdbAtkLbGjrbB6XREw5Ctoksw3CWC7L8j4/JYYYo4Zjusc4l6qDRZ2ljFWOtEGf7xb97fBsWZDEmkLlFuEa7Dhynp3/AAQfUIWlizzVUkM4nsn2cY7vKkeWNkCROCPpBqChnR1fAi4PfKn0TJffee+/62W+//ap1UvxGOr59ZxllQSK+LG/F4kJEu559kB6e3fxOy48tf7Zt8pL8Rfwa7fByiE033bTmKfvbsfKkF5/o0LkO2jXhGkSv0RZ51EiVc1v+dpyPbZ5HC4f8rgxxM/rEJz5RXZaI+Xase/iEMF4YKdERby4aYXyIQA5hDGgkNW7N50tj1yyigyJWCAANusYcrFjehuQtRz7eYER8wTGO15CDcNaIi6fGW0XL8mU/Yea/7fYTCOLMKkZgsJq1YbN2HfsIBN/bNulH6Lk3qxvLHxcEw/a2uYfhPPsIblYRQ9Vd68KgIW2keRtFEEf5Qly83cpb/ny8ceqlL33pLPHf8ozz22/7xF285TPDtZ4BKzorqM4FK6TP/N4QyoPS2Efa+S8dlUvpaPRE/uc3z2WH6wWU19bRgA4g4eu/NGa5aiLWNsP4On7cOVzDfTwj+ZuAdi2C2HnOYVnmTsMH2fCv52f0SZ0hH7u/74NSZ4wF6SF/S9su4jvSdrRzHNPFb2lo/+yQRuqFVq6mEvFrdWAr2+LRyr66q3WaRqPl12YU6ObB8UB9wfXK/8nEc2zlDi2eo+Vv6dY93nHScFDLQ3yQw9AzGT7ICjZ3AsPjGjy+ZwQLCyd3A24E443KZiw+yFDhCCP/Vb5bc/IPVUE7jmAmXlXahoYJL75vhvPhvoalNfS2iy+rprg7xodY4HbBJULlZwjakDchQeS5j7QjEPgJu44PUa1ydH2uBK7hOGnrmRInzp+TBXkqfZA9I+kn7E0MSSOdhZFErGdkv+OlkeOlD99MgkvasfxzbfGd+OLryr9WekhTaaVz4Vy/J5NB8UGW7sqcsscC7BnIy77LW/x++ZvKj56FkQ5pryw5Rxpym5D/5Hv5XCOt/rDfs/T8xLM9s+YzS3hD3lcWdPr4kKob5FdhcL5zHatsKhu+Kzeem3wunK43VYzVB1n4dRJ0hsVJeTTR6uijj65iSFr3l1HCievVV7/61ZpG0gbmRMg/6urZxV19xMIvzaTnPeWe+CCLiwm05kQQuDpADAW+m4shDXSGoByPhPLMP11664iZ9Mlnt5vubQ6DOnxuy7UwGCGUT51/T5Hnx+KDrMyYTMxIojypty3PZgRM/u5H576tfcx1SXr4rYzObRvq3PgghzAAaGCJFJU1/1yFW6HWuGgAphqNjcadSGzidnY4Vtg1bs4lSsWvVTTi2fargMSRiNBAauQ1NEQBUeJNWASASt11Xcd/+51DlLg+gUcYup5jVaCuYz+xTPRBBW8GszSeSgExFjT80lxDzoooDn4TYCNBDJvgJZ0JMPmKHy3R5LvrEHvEsw6FtJEWRJz90sZ3jZHnML9CgMqfRIY04RvPZ1ingp820SpN+cJLKyiv0r6JGI2/a8irnpu0b3m2NdaekWPayIb/jnUOX2blwznytmclD9iunDieYHG+sLmuciR8wiSMw4BwGsXwIodmiTf50LrrVrEZqQOr3OrEEG1cTEBEmWhKCDYIMZ2YfjwbIwGEH4jUZnX03bX9x0RbH8XFqA5fdc9RGWbh1ik3CVmdJk4mbzMWjISOmPiLq06U/y3e4iEdoNx307Nt7x6DFveGukKaCBd8Z01uaTaRmLxqHX6TwdV7OtE6DyMhL5mcvO+++9a85DkbLVRuILzSalCIQA4hhAGCwLKKB/Gtk2AymYYzhKlCZ1ZHjbsK665VW3QCdOYIMaMcxC8RzarKUqgzwFLOxYqINdKjY6izTAQSSAS081iaQTxxi2FtNdGSOCW27Gd99pIjrlsnnHBC9es3t8JqMRONskgI6xARc9b5JQbFUYepjZARgCyvwiktfLwESYdOR875rM9WqOESsfvuu9c04P5mgrI4u759LKteOsQNjfDlpmW1FS+a8YInQpI1+vDDD68rpOjECIMlCJ0nDD6jidXxwHM0GqDTLg947s0aLI94TtLAMzYCoR5Tv8lP4kXoM7LYLo5euuQcna/ROhuTSQRyCCEMEBpIllEWR9Z2ltAQphKWPdZ4bhNEnOFteZMVVX4lIFnLCR+WdEKNxZN4JCSJPWKaSCSKiDuCVx6X17ktEMfEUbP8u45jWV5ZJ41MEZt+uzYBZdUYQn2iIXwN5xOpzYWgiVHWUO4XXtTBIkocSof2aaMRxCPf9D333LOKQULSkoJG0ayQ4nrcT6SpNfZ1PKSPidbSgf+zeEsH1mzP4Oijj67Xb6sOOY7Q5qrhukanmnV2InA/ItmomTygc+S37Z67Z9jSwfMXfvu9RERcdZrkLR/LX4qjUR55jICeaiKQw3yHikUlYghvdhjes/KC3vxkDFUNKxpNFp82vBfCeKPh5DOrUWWNZDnznagiPOaE8qvRtV4sC+RkQMSw4M3uzYrDBLcr7lusfKyAhA4M53sGBKu0bRN9bWd15dLiHN+JuLavvaiIRZnIUye7juMIK/dznCF77giW7TNfwX4WR6MrRDrr5UQjzKzEhF1bZ9i25kIjzi0fyqvSoaWFdoRgJKqJ1i233LKex0VKPLnbSAfi2rZ2rnaKTy/hzZIuHaWVNHCsY7h+SAeWbNeE9OD2402lfH1HmgsxnnhG4mFCtc6LMuaeBL74t/hIF/HQAdA58HppHQb5RvqwOLOwc18Sl64rzlQRgRzmO/T2vQBA5TE7FHJLdBk6ikAeHZUe8aIyD2G88YKagw46qApc5ZYo1ghbvo2o+sAHPlCtbKPN4LfdMLzG2OQoQ/iT0ZljNfNSEAJvTojPIJef5udLrBE7fL65WqgXCWV1JZ9rH98JHucQTwQd0Ub0ONZ2dQZRRQS5Dgst0cSyTDC5LoFIhLI8EpdWgXF/VmiC2XXcZzIQDxZeItWa522bj/kXLLXcHDzDlg4tLcRVfMRFPKyPTdCKg22tbfFf/J3nHIKcWwt3DlZg+9rxvttGUOs4SAsdMWKcALX+vbkhLO8Tndfdz32JfO4WjErCL726aSG8wi+syqSXS4mL5+94Fmg+7Y5BW3FpKolADvMdGi6Frw19QYWjIvFhCVDgVdoqZ71236FAszxrpFmIVJCO5/+lQmcVUfHxu9N46+Er9I5r5w2Cb9VY0BAKrwpY/Jovm/CzqtsHlb7Kr1X0IYwn1o9mMSMUdttttzpJii+rBph/9g477FCH3g0rg6WqlWXlmnCQX02w88IWw9kabMdpzK0aolHWULNKm3TkeNYvnWh5X6MOZZtQJ+xsUzYc63zlW5khGFxXeXEf9YOyYh9sdw31g+/CyMIq/MI8WaJvrIinNLFSkKF0nRVxbXUeEUj0rbfeevXFKJ6J4XWdZunH6sxXmPVYenlWnt3mm29e481lgSsGEU3U8Tf+6Ec/WsWfa5jUyGLsFcqG8N2bEHUdz2Oi8Wzdj2HFvYl8dZ34e9Y6QXyKbRMXQtFvaeFj4qg2gIXUc2/1pImOzXIK95CX5JONNtqoTgB8z3veU90w3EdbIt+pf50j7TfccMPa8bOcp+fADURni9uHjpl05f88UQiXdFGGoPPgeWnvWLZZiaWBvMHy3p6b9hGs6azG2lflUrmxdrj2xLlTzQIzH9BglcYQ5hINjYrWSwEMYc0JLgGWLdJYamxVWLZpiBVUDYLKWoP83ve+t66woLerYtRomnDgHJWUyVSu8e53v7sepwF405veVCdOqChUcnyqXM9aqoaP/DfrVyMyO4h0FR8fval4Q5JXKAunIUCNgCE0bxjzYhCNnuG017zmNVWsnHDCCTUtVIqTjXWGiR3PKkwsJtoQAdtss82YVksZDwhHk5JYLTWaht4JJ69G59sKk500tPIqi7MyrGljqSNWTITS+LKsKYv2yy98PF2LiFF3tLXCiVqNNCueJcKUP+WYb6i8xsWDdY9Icr4lyXzUC29961vrRCp+tMQA0QvhUZ6lH0FBbImLMmXNbNY3QlM90jrkE4kX0RBpOh1TuSKKNGNBbPT/bki/5tYxtxDormnUYboxUroQ9dJRHp4XdNrkVe4sROxkMtrz70fe1c7qTEyUH3osyCHMhMjVMClo/rMao7//aAIJsaxHrFFhnbI8FLG71VZblcMOO6xWViwbGnNL+mh8iWJWMMtB+U9IDzosPhptDfhmm21WrSAqL28la0vdaegnozEP8y98PAlIwtcEJwK1H9Yzope4bUPePnxUlU2v9WZB5pdp2bG2tJTXqhO/OsxGi5RV5dtrw13TfmVdPldmDVkTsToHLH06ja5vyJhlz3EEsXJDQOvkqgfe9773VeuZ8qPsrL/++tW6x8Kq7iFEXMu++a089Yuh0cTRvIrj6c5I6SIPzas4nmrGIo4niwjkMN+hABriaxWLReA1dizCrNGWHyIG4RgVDaFsmNFsa75meq+GiVphJpzbdz5y3Dccq6HUMLehVx9WLJatQUecxYtQkF7SgdXL7GJD0Rp3FbE0av9DGG8MKxOQ/Iy5NSmj3fLLNcLIjtEZ4tl+ZdnHMLP9LMLKneF/fsi2t/Pla2VXfucu1HwmWXfla8P7/jd3KmJYJ5pwNxmKm4Q1cAlcYbAUGv9aZYd4dn1lyD1Y9ljhuSsQ3C0MOtTEcwhhcIhADvMdhlqJYJYk7hI+3ARYbwyz8rPj1mCYSePMB0yjxzeKFUsDp7HTuBHNzTes+WFpSFmLDL0SxBpFjSmfMUOyGmcN8aAjDhpy4p5vnPiwmOsgaPTFU7ylJ983IiWE8eYb3/hGdbHQMTPRy4f4bW8kO/roo6srhNEfFmTiVVn24Q9KiBqK5dogvzpWGZe/bVOeTQBj7ZXfdXz5DHMhIrjNKyC6m4VZHUCoK9tQZxgh8t9oEpcQ7lk62c1P1/n8T4XFclZtYpp97mFeBHcsrl7qixDC1JNXTYehpwk51loWnDlB3PJXZOllHdKwEcQaKZYf/1mACUCNMeuVxlHjq2E1NEogGr7lQmEShPNd03dCUmNojU7fNcqGbV3TvdvbmHyfHe4/1ldNTwSsdMKq0ecWIn4EgtnmLGPSwYc1XHzMVu9OfJwspvJV0/MbOndGD4hReWIykNeUU1Zdfv3ymc6pvKhcKq+evRUGHKe8tHKsPDpPh1R5Uz8QzjrEyj+RqlwTyL6bSS9PtxdDcCOSp5UB25UBec3+9kIE5wsL4a28+K8+4PKh/nCeOLiWj3rKvRxndKmVMVbm1gFoluWJRN1EoOu8S6PpzFhfNa0TprMvj+usQBqZj6FTpJ0xiiBv9MPFRmdLujKaONaz9eznBkYXxhYdJXNr5GujGbPDmtKO4fOuPtTB81+chaFhlIRxiDFD+RgN9x7Lq6anEs9lol81nUl6YehhnZmbSXoTiYrFLGzuFdtuu22dvKaSmZeJDlM9SW9YyCS9yWMqJumFiWEqJukxZhCrDAaMDJPFWCfpWbda3b3zzjvXvM5IYT6KUTN+4+p3ln5LC47UiTFB02ROc01MIOV2M7cCk7g2OuI8k7/NbeFPPxoE+/bbb1/jKOzWpLccov/cfMwfaZB7RkSlPV/90ZjKSXpjJZP0QhgyWIZM4rG6A9cDyxaZ5BZCCPMTLOgEm7fPWUue6GIwsA61VyEbZWMpba9Ktn+qYb1nTTciZgTw9a9/fd1uJEKHkNXfhE9xa0sJEqiMGQ3nGikg3Ihr1mdpwA2Hn7k5L+LLtU9acMUxudt2sFSzRhudYOUl7Al3acf9x7JuOqlt3W9WbyMrDDHNb57V2fJq3I2c21aC8Z/rUBgbEcghjDOGX1VMPs0FI4QQ5ie4CvAVZ0VltbRUJFcxbiqW3oP1ei2H5zi+5lMNActP/JBDDqluC23yNYsui6xVVAhX7gssrNZrtjTgiSeeWM/n4kOE2m7436Rm7hrEtu2+s94SrcQzlwjLA3LRIXQZVeznltfWeGap5qbB8k7AGy3jIiFsLMLm0nCT4RLnN9cD4T/++OOrUDd/RAelTTblImRbmDMRyCFMACo1Fd2c/IxDCHMHEWOo3kS3qYRQMYFVeAzFsyrOLVbAYC10/nSDv7cRNM+KaCP4GAuIPT7ibRIj8UywTcZLP+aEepvV1uTOZtjwfBk9uE2w0DrGd+4aXlKz66671pdcwHPkc84vFvzUvTxD/ORXVl9CluGELzp/ev+d477yE19092jer76zENvH+usaOhXg58z/lsUYzhFG4W9uM+181nBGG9fPRNCxkdY7hBDC0EBI8QH1VrXxhLghWMcqVi3txorISmhlCxbCuYWfKwska+t0g3XUGgCsliZJEmXEmo4FdwpCj7jjI+uV/l40NNUQw8LLP5efPYSbqDUZU3xYbj1rvtvWt95ll11qXmjHEtMEMzc7LibW3ia2pYHrE7HSwYcBxaf9bvubgJUX/SZ2+dkec8wxNXzcOGBFFGLYZFU4H8K/xRZb1O86bt37tHuEOROBHEIIYShgbTUEzvLWILSsrsFS2Rp+fqGsdo6FY/h2tqUIWS9dizA1nA2TfviKmr1vn2F1PqaGvYk639v63/DWPkPeRIwPEWP4Wlic47rNyu0c25vwIVosmWiUifWvCZvphLRgLfZfp4Yoll7+sxpzVfDxdkJ+tSZbTzVtRECYG56VjlPzMyYyrXrCj5rv8FFHHVVfLOM8z5OfcBOhnj+LrvjLP/KJ7/Kj6/rvut17yCPOczxhLi/yiyZ65VHuGpDf5UsuK8LkfjprzumGn6C2vYlt93DfMGeyzFsYelQUc7PM27CgQpvKZd6GhSzzNnlMxTJvDYLSG++IGOXdDHsv6uCDKUzygSWtiAUrCBDBLHiOI8gIZH6hrJbKFVFGYLDCEW6O5wdKUChzfFAJW9eF/+Lv3uoZQsM1lU1v2CNMDF+beEWg86k1sYvQtpYydwKT0izp5k1+rkdIq7+sUjDZ6TnRy7xJU+mo42BpPZZX6Sb+RLI4E30EpZV6vAJ8ohjrMm/ygzzFX1e4CUr1MJHLgjy7+STSUt4i+ll45SO/5QudIO4N9rk2K7PrOcY++bZZqd1Lx8K9pJdzWJ/lKVgBBHyihVGcCHNhJar5M7suq7L4uJfvluO0XV0pfD7SZCSI9CzzFgtyCCGEIcAwNnFhghcRo7Hnk0kME2MEJ/FKmBITln1k6WN1cy5/UEKWOwThYRUFvpx8Pwlpk6aIAa+WJnqbtdn9WOkIbUKPaHZNgoYoIYoJFUKYoOBz6j9RQiCzNDqHUDnooINqw24FA/65XkdNCE1HC7JnRRRKS8YLQkaasf5bCs2Qv7T3Ku7mszvV8NX1jK2RDQJSXjPRsLk1jAYBKr46HAQrpIE8tuKKK9brmDRn5MGLZAhh6eB+vrtHO8Z++VEnQp7UWZNvmxuKfCcfScv20inpqcPhes1QJF9ywRAvYXGM8Ain72H2JIVCCCEMPKy1ltkisggKDTwRSyywwhnmJhCsI0s4sIoSI6yVxDTrnGNWWmmlaiEjRAg01qcmUF2rQeQQNiZQuT5BQlS31QOIpyYy/HcP1yNKLOlFoAsrix0LIZFtQpffBDPBRVzP7YskwvyFfEYkv+hFL5q19rg8xM9Z/g4TRwRyCCGEgYfANamNbzGXCcKXpZYIhf9EMRHd3C5YjAla+4ha+wlfPp+Gn23j++laxCpfTZPLmk+oDyxR1oa0+TUbdm/HENfOJ1pYrr2AgxWxuX6xJPMpJZ6JHRY/4RBGbzXjttEV5iF0kWdYmlmXGy2fz87lI9xzIpBDCCEMPG9+85urIDbUbBiZFZil2GoB/Ij5shIOfvNztY04NrzMbeKb3/xmFcBELmHLKuy3SVNELKs0K51JUfyFWY9Zeglgw92u4zexQkwTwK5PHBMxLMgs2gSwaxLHhrXf+c531vt5uYN78sv1somf/exn9RxhbZP5Bh1xtWYxS3qbcDgSOhAs+V55rOMQ5g6TR7kOyW9h6sirpsPQM0ivmh5PTALKq6bnTF41PXlM9aumzb4nWAlPwosYJdRsJ459QKDaz32BCCXYiFTnOUbZch3fiT4uEva5lt+szL5rHptLhWv6b59zfVzXfvvQrmdfO5f1WvgcS5wT0y3M7VqOIbonk7l91bQJhepZHQWdFKsptPV4u7Cie9UxP1edAP7H/K1tbxPTJpuxvmp6UJB3vGK6uQ1NNvJwXjUdC3IIIYQhgeA0q5+g9J3Y9N1QcxPHIHZta2LMMazE7RjCmni23X+/27X8JlZtcw/Y134Tta7jN2HpHs7pXs929/cbzvPbdeAcxwinfZMtjueFtqqBVRQIN5MeCTliqn0If9Z31nyvOmb1N0nMm9y4qHBP0Zm1mof/3Et0ZHQw7GsTI4lpVmrHEObcWeAerKv2WdVEp2MYkE7iZKWUllYtDfy3+kQ7znfpIG5+h6kjAjmEEEIIs4Ul+Pzzz6+rhHAVsVKC0YRPfOITdXWOAw88sLqVmPRI4Fm9Q6fEBEWuFpaVO+WUU6qLxsYbb1yPd54l2FzDEn5GgSyJxzfbiy4OPvjgav1luWZpP/TQQ+uKJF757AUrlvwbBsTxU5/6VI3HZz7zmdoZ2Hbbbeurtv3efvvt63FWU5EWp5566qz1ucPUEYEcQghh3GEB82k+qKyL7bfvrIJzsgCyoDnGsQQS2nnjYV1zTatTtMl4UwXrYntJxbzCZYPltllbxxuWYK9N4Mv9oQ99qFo/vTKZ37ZJidYhZ1XmRnHAAQdUQfye97ynxs0EM8dwFeMywGLON3ufffaZZVV9xzveUSeeEYlWGGGh33HHHes5JlyKG/9w97MSSfcNcoMMi7B1r1nfuZqIr7jpOKy//vpVKMvP4mddX3HfZJNN6v9YkKeWCOQQQgjjDmHgddBWnCD8WM1MPDIEz4eVxZAYspoDcTASXBJYJU844YQqLAgGftAskXMS12PBNQz9n3baab0t4wfRN1axauUMLxiRZtLinHPO6e0ZO4bqrZfLbWEi4NJAmHp1MjF+xhln1M4FIWyVDx9hJ4itS80P2drAXshCEHefl+faxC1/cG4rIBybGwpXFX7D7VxWa2tJyw9+E9pdt5pBRT5gUW9+8uuss05d0UQnURqIr7hyM9HpaO42tjcXnTA1RCCHEEIYd/jYGir2Mg+NPaFAIFvFgcghjPninnfeeXWi5WgrObAaEtr2uw5rHDHYJrg14UU8N4ub7e17d3s/zmXJY6Fs2Ea8dCF0u9foHtM9tn1nkbbEnJUc0D23WYkd2wS0NZF1AIhF8eRjC+eNZFUeSXgTW9JYek0EhK7XQnOB4E9tApcPocqa6yMtPVvuBKyh4HJhhRCTqb2pkIAnorldEMDWhyasdZas2sAq7bcXr/hY1o8Qt2qI589Fw/35oo/2XAcJlmOrrRDJno04eMY6HPKHbfysbZN+OpQ+8oA0GoY4Tlfyqukw9ORV0/M33qBm2D6vmp54iJuxvmqa+CXkiBwrH7SlwQwzEzmsY69//evragd8MeVxwulHP/pRfSkIQaUMsFoSm/Z7wxm/V8PzJmuxtLoWy6NzTAYjOrgBuBafWeLE+RdddFFdEcZ9heOrX/1qFSn8Qwku4WAFZd0WhvaKXj63ru0a6hdihoCxQgNLIMu4FSH8P/fcc2u8WQP54BJ2yi9rq+PlVaLHdtdoYpNlkaCUrq7vGu5/yCGHVLHNwi3ctvnuGZjFr86TvjoihCRr7rOe9azq5jAn5vZV08IkTYXDy1Okl7ATdSzFPs3q2zozVjpxfdbfJvSJZenYhLN98hKh6I16Xooh/Wx3vutZZs/54uxc2zxj6eXZz4mxvmp6IpBu8q04GSHwXb7SgdQx8kylo7wpr8rzRDG3FHF1jPhOJspHXjUdC3IIIYQJQqdF55UwIFYNLzeatdWQsgaO0LNNZ6d9CGzijW8rwUz8ElXgTmAFCMKQQDQ8TQg1i519RDBLM3FOgFk1AsQuscUC6npEDAsf0UWgsFC7Jus2IUuoCaPrEMzCbCIZgU54cdMglgkZVnJh8Ju4IVaJXuKb0GvHEfwmYrGkt2F1EFLu7RjXYQAQBqLKfbiocGE45phjqnDXYRB31yYWJ8riKLxedWwVC89Vmo2ENN1www3LmmuuWV7ykpfMWsHDm9+sbGHd50033bT62IKodj37daTEQVwcI81ZqJ0nbxDeOkyszn4Pi3VV50GaiJP1teW5DTbYoMZF3uZz7L/Ohk6jNHa89BgtncPEE4EcQghhQtDgs6Cy9LCwsjyOBFFIABI8LIXt0wSQF4MQxyeeeGIVSwS3IXkQH8QWMUk4saAScob8Ddcb1ifSvCykwZK73HLLVbHmP5FLoBPALLZEHsHCkuyarFTEPfFMqHNlMKGMlbN9hJFFk5VVWFgKCT3fhdF9rBts/WDbCGwWbJ0A92+0V1BLt1e+8pXVau/lJ+7HqufeXnBCfLqXdHFf15fereMx3fAsPVedAZ2eHXbYoVpfQ5goIpBDCCFMGISjpaxWXXXV3pa7++Sy5MKQMlFMMLYPQQrD+dwKiEHWYVY1lljfCVdWRttYXZvYNIRNOB511FF1H+HZYKXk7+r6fH9BdLFmuuarX/3qek2ineVZeNvQN1FG6DuGBbB7T+FvEP3ELJzXwmdomOuE1RiEqV/QdjsGrMss6ayO/HKFzzksizoKRDiEkXVVx6ErtqcTfI51erhJeDbN/SKEiSK5K4QQwoTh1czE28te9rL6m3DkWsCqvN9++5Vjjz22vuGM2wArKEsv8enNmIQhWIANt7sWoenYNdZYo7z//e8v+++/f7WycrXg59sEr+Ncj7AilLsQl6yx3hZGoBPfrMDEMfH6gQ98oLpFsODat91229U1e/mJsjpbm9dqDizAJiESqHx6uZMQsqycrscNhAWbtZi7BtHPOkz0egsYP2rHc9VwDNHOus3aLn2OO+64Kpilk2Pe8IY31HCbOmQ9YGKdYDQp7sgjj6xpwD1kukIQc5Npq16MJzoqPjpCc7LC68B0j20dmvHARE35Y3a4rzzm/5wQtm7HLYydvGo6DD151fT8TV41PXnM66umCWRCtdG1krJ4jsUSSFibIOYD5zchwU+5CQHCGPIEf11+ydaa7YdYdbx7+9+uweprW/MLtk9ZZHW2vR0j3M5pcWn7fITBdgLG92bVbfFswqoJPfsd385r1/Pdvvbbd+eKN6HY7ul39x4tjWbH3L5qepgZy6umrdJx5plnVrcY6akDZoRgJHREvMSEq4xnZiIb95mxTHacHTp3OkV8svvvLS/Id/Ihf3YdQ2807I7MjITOqI4b1x6+4GPBffKq6ViQQwghTDBdcQxihbDw8X0sEIRd4UcQEiRNlPjteiAivYSC9Zbf6kgQp85t/+Ea7tOdNCd8bXUGtGPaOS0utrfvbbvrtDi28yEezm/bu2H3u12vndt+w7ks6u16truWe/mMRRyH/4WLDz/0d7/73XXkgtV+tBfI8A+X7tx7vOzDmt5EKPiHGwGw7jF0YHTWXNt/uK7Rgv7rG43wXK1OAhM0fWBCphe0EOfcbAh513M/nUf3MdHUNufYDh0x+aXlL37rRj78D7MnAjmEEMK0ghhgNfYmtrEseRYCYUpkstTqNBHB8hG/d+4tlvDzaS9iIZDbSAJ3Gp0owtNSgwTzYYcdVo9jwbWaCsswCzWXGkv1nXXWWeXoo4+uoxMwosGtx4ROVmL39GHpt5Sh5QFNGnWe44SVSxH/fqubsHpbYYW7jf+sqyzSBLXzCWX+71ZZET6uTWH2RCCHEEKYVhAtBE6z8oYwFlhijToQmJadM1LAv5zI5S/uv1eCy19GKfiJn3DCCdU/foUVVqhWWattWOvbkoEsuZbsI6Tf/OY3V594Atpa21znvBHSWxRBiDuenz3rMv91ri+ELyFtJRU+8ptttlm9B2uxVUu4TrgOASwc3IqscEJ4E9TWUhYHYfC2Rte0rJxrhdkTgRxCCCGE+Rqil3sKSzCxSQCjubh0P2071wXWZmKURde5rLYsyfyTiVjfLUNoQqUJnoS2dZCds9VWW1WLMViFXcvKJMSy84WBfzPBzbKN5lpjv6X/uIYIk/tzsbGN7zCrtvMdL17+m69DaPNFJqzD7IlADiGEEMJ8DUstQWmCnNVLvIiFxZgINhLRPkRsmzDHkssHmauDyaCsySbQcZfgC+xY/vf8k7lIcHcwssFSzYeYiCWQWXitltIm3HELMrHVUoZEtVVbCFyi2rWIcNcQXvfiy0wgC1Pza+YD3d0vzMQ3tw1i3It7wuyJQA4hhBDCfA3LLmutZfKss2ydasK3vaDE8oPEsN/WmyZa+fQSsJYNZPX1nSAmtl/xilfU/ZYsJG75L9tu1QWuENw4uFIQ3azMXlLjtdxgBfZyGK9Hdx6RTiy7Jisw4e43CG+uGyYGmpjnBTfiwJrsPGKaxZhI3mKLLaqwthqNfWH2ZJm3MPRkmbf5myzzNnnM6zJvYfDIMm93h+hlZSVYTZJT/xK00sa5XZqllusC8dl+c7Fg+eW7jOZ24dosudwinONYx3kRjWtb05q1901velM9D8LC39n+9np14XEu8et6/jvOuW0bfCeEWbCFocXDdiLacSzZ/fFqiE+WeYsFOYQQQgjzOYQuAUscw/8mYPshoonWtq5w++0/4UkU+7Am8212HRbftgSffVwrCGlilBhfa6216r6G+zqniWMQuHyZnS+srMDu0b67j4+wO84+wliYnAvHNpeNMHuSQiGEEEIIUwARy/WhTdYLg0MEcgghhBDCFMDC3FbGCINFBHIIIYQQwgRj0p635XGpaL7DYXCJQA4hhBBCmGAIZMvAmTR3wQUX1BeNdNdJaN+zdsJgEIEcQgghhDDBsBhbi5gA9vppr3y2Moy365100kl15Qlv3rNWcVuRIkwdEcghhBBCCBOMtY7POOOMutSalSisgmHVib///e/l+OOPr8uysSpbk9n3MLVEIIcQQgghTDCWV7PMmqXXWJKtcf+sZz2rvpRkySWXrJZjr6X2QpAw9UQghxBCCCFMAlatADcLLwvBIx/5yCqMP/vZz1arcpZ8GwwikEMIIYQQJpirrrqqnHfeeeXaa68tK6ywQvU3PuCAA+oLRliTWZef/vSn944OU00EcgghhBDCBPOa17ymHHvssdVa7PXIn/70p8tWW201a9WKVVZZpTzmMY+p38PUE4EcQgghhDDBeN2zN+d5MYhXPZugZ2WLnXbaqXz/+98vr3rVq3pHhkEgAjmEEEIIYQqwmsUOO+xQ3vWud8X3eMCIQA4hhBBCmAJYkx/96EdXoRwGiwjkEEIIIYQe1in+6U9/OqZXQXtt9K9+9aty3XXX9bZMHtdff3058cQTyz/+8Y9y5513lp/97Ge9PWE8iEAOIYQQQuhx4YUXlo9//OPl97//fW/L6Pz2t78tH/zgB8tFF13U2zJ5LLTQQnWi35/+9Kdy1113le9+97t5TfU4EoEcQgghhDCTG2+8sVpil1hiiVmil/hkTe5+Gt6Cd9NNN9W35LXXQ/t/2mmnla997Wvld7/7XRWtF198cTnuuOOqZdr13MPrpn/84x/Xcy655JK6BNz5559f37bHIn3KKafUyXusw873IhFh8opq9zXhzwtHCOXLLrusLLzwwnWdZcf/4he/qPdzfff7+c9/Xs9j7Q5jIwI5hBBCCGEm3CuIzJe97GVVtIKY3X///cvHPvax+vnUpz5Vt7PcWtP4jW98Y/3vN/bee+/6qmgfwpbw/cEPflAe8pCH1LWQzz777GrtXWaZZaqIvuCCC8ott9xSPve5z5W//e1vdd+BBx5YFllkkXLooYdWFwphOuigg+r+yy+/vL6a2jarYcCKGK4LIvvcc88tiy++eLWCE9bf+9736lrLhx12WPnrX/9ajwuzJwI5hBBCCPM9LK8stjfccEP59a9/Xa20V199dVluueXKZpttVrbYYov62Wijjerx9hGlzvvJT35Shae34/m+6qqrljXXXLM885nPrFZcr5l++ctfXl75yldWserV0k996lPL0ksvXQX0/e53v/Lwhz+8vnbaahYsw89//vPrS0QIZNZigplwd+2//OUvVZSb5Adi2HF8oonyhz70oeWlL31pWXfddasAv/TSS8sPf/jDcs0111SBHeZMBHIIIYQQ5nuIS+L1TW96U3ne855XHvjAB5bf/OY31S3iox/9aHnf+95XP/vuu2/5z3/+U62zXvjxile8ojz+8Y+v7gtEK6sutwfilah1LKEL2/3233HensfSzA2DSPZxLGuzY5xvH2ux7Y7136oXtnV9jt2Pe4frOw/uQbS/8IUvLK973evq66y9kCTMmQjkEEIIIcz38O/l6sD1Yfnll69i1YQ9gtIrobkn+HChYIllbbaPyHU8SzHxytr7la98pVqX+QI3K/Hpp59e3R+8Ztp1XYP4Zim+9dZbq5B1/9tuu636QhO7bTuhaxvrL9HOIs1K7Bjb2zFENeu0+/Fldj8WcP+5inDpcHyYMxHIYehplYL/0w3xakNoYWSkj3QKE08rayxXYbhp5WZ+eJbiOZY6gquE10FbPo01+TnPeU51keByIb2aX3FLsxe84AWzvj/pSU+qVmf7P/nJT9a35jln9dVXL+utt161MhO7T3va08omm2xS1l577eqXzFrtHosuumhZbbXV6uQ8opvI9X399defdQ/hI8If+9jHls0337y6gGy88cY1bnyn3/GOd1Qf5de+9rX1rXziwI3D/Rz35z//uYaZuJ4d7ueag9z2qIsmOnwLzOja56cAQxR8ffSYQphbFGKTHk499dRaOenF61EPOyoolemXvvSlOpta5Tod4jXeqCBZRDQEG264YW9rmAg0+CxsPvwo5UsNdhg+PEvWRe3vBhtsUC2lUywFJgxC6stf/nKtUwlHKzqMBnGLtkpFE9V+96ePuse1XU85cKx7tDJhv3Oc2wQn2rXs93G8T/d6jm/Xst137dzRRx9ddt9997pNe2C77y1OzneO6/ffz++232d2uLa2h080IT9obY+4XHHFFbUu2mabbcrKK6/c2zO+TLlAtn7gMcccU3s5UxyUMIQo8IaLLLFjUoMhp9lVgMOESsxQGl8z1oTpEq/xRANhGSWNwLLLLtvbGiYCZY3FykSkxz3ucdNaVE13PEsTzAzLcydoYmo6oo5Qj/ovrsOaZz0zy7jxL55otDXSjB/zUkstNXBtj7Tg682VZa+99iorrrhib8/4MuUCWeRUtN5DHsK8oCdpeRxDSiZMTBdYRffbb79aqbdZ0+F/sVC+hn6HHXbobQkTheWnWB632mqr2mkLwwurqrVzt99++yo0pjNcHoiq6IyxYUTfRESuHFbvGERMiDzyyCOrS8xEtfsD4bTJKT2EeYWlVa+aFXG6QSRztQijo/6QTmHiMdSqrGU0Y/ghgpSb+WEUQB0RnTF25IlBb3u09xPtmptJeiGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA4hhBBCCKFDBHIIIYQQQggdIpBDCCGEEELoEIEcQgghhBBChwjkEEIIIYQQOkQghxBCCCGE0CECOYQQQgghhA4RyCGEEEIIIXSIQA5hLpgxY0b597//Xf71r3/1toQQQphX7rjjjnLjjTeW22+/vbdl/uTWW2+t6aCNCYPBgh+cSe/7lPC9732vLLDAAuW5z31ub8vd+fvf/16+/e1vl1//+tfliiuuKDfffHN55CMf2dtbyo9+9KNy0UUXld/85jflqquuKssss0xvz/giHOeee24577zzyh/+8IfysIc9rNzvfvfr7b07V155Zfn+979fw/yrX/2q/PznPy+//e1vy0033VTuf//7l4UXXrh3ZBgPrr322vLjH/+4PPWpTy1LLrlkb+vcQfCeddZZ9fl6Xn4/5CEPKfe5z316R/yXG264oRxzzDG1Uvcsv/vd75ZLLrmk5oVFF1205mXYb7vrXX/99WXxxRcv9773veu+seIarv/Qhz60POMZz+htDf1ccMEF5bbbbisveMELelvCRPG73/2u1sPPfvazy4Mf/ODe1jCM/OIXvyh/+9vfyvOf//xy3/vet7d17vnpT39ay6B8sdRSS5WFFlqot6dUwffDH/6wttMLLrhgrVNbHdn4yU9+Ur761a+WJz3pSbVOlce0teeff35tP//zn/+UxzzmMb2j54056Yy5RX1z9tlnl0svvbSm489+9rNa30uDe93rXrPiKezf+ta3ajrMLg633HJLTQM6hoYRd+3QxRdfXK/v2nQF8axdOPPMM8vll18+a79w0CXaikUWWaR31XnnzjvvrG2PMv7MZz6zt3XukEbC6RkKM82EP/7xj7Vd/OUvf1nT6QEPeEDdPrfIu/LO05/+9HucP0Zj4C3IMtspp5xS6Pj3vve95bDDDuvtKeUvf/lLOeigg+r2973vfeWaa67p7RlfZPpdd921HHnkkfXhHnHEEWW//farmXokiKoTTjih7L777jW8hPJXvvKVsvPOO5dPfepT9cGGwYGA/djHPlYreQ2F/5/4xCfK1Vdf3Tvi/9HR+cY3vlErcseq/DzXL37xi7VCaHjGe++9d72uiqxfaIcQwnSA0eozn/lM2WWXXcqFF17Y2/pfiLwdd9yxfP7zn6/1rPa8i3O/+c1vVlFMQBF8+++/fxV7jlW/7rvvvr2jBwdh+/3vf1/22GOP2kHQFhhZpEdOPfXUKjBB1G633XbVqDI7/vrXv1bNwIrO2CIdaZ4//elPVWgzzBxyyCHl5JNProaWk046qf6+7rrrasfDfYSFkXBQEG7i+AMf+EB9htIHwqsz0E2nQWXgBbIe0QorrFDuuuuuWpgIFL0pyETEp0Q2PLHWWmvV7eOJDKsXJEOyUL7//e8vSy+9dH24owlkvRnHEEyPeMQjyjvf+c6y7bbb1uNPPPHE2jsOg8M555xTvvOd75Q3vOENZZNNNinbbLNNedaznvU/lg7P02gGK4n9LMaPe9zjygMf+MBy+umn1xGChnyqd/vwhz+8POUpT7mbVSWEEKYLq6yySm2nm8GgiR7tndFdo6/qyWWXXbZu78KoRRS/5CUvqb+/9KUvVdGnHn7zm99cDVPdEeNBQX3+vOc9r8Z11VVXLa95zWvKFltsUTbccMNZ4WU1ZbkWd8YWWmU0iGzW4Ze//OX199Oe9rTa/qyzzjrl9a9/fU2LzTbbrLY10poW0f686lWvKhtssEHVF8IzSKPThPyLXvSi+t8zPvbYY+t26UMjsfw+6lGPqtsGlaHwQZbAMoVEVXi4L8CwzYMe9KBZwxl6JpDRZMZPf/rT5fDDD6/DFjDccfzxx5cvfOEL5Qc/+EHdRnQTrI5jOez3gyLMiW8WQMPuhLFrK9Czy4yOFx4FSaZWOTz+8Y+vvahm6VaBuN7BBx9ce1TCJ+yGHo466qja6/ZfWLvWyTC+ELbyj7yFJz7xiWXrrbeuFVsXx8krrTJvGKKUb+QfOE7nTSUnH/RbTUIIYTqhneTiRBD/4x//qNtYWI2eMSZo1/oNDrapM7Xvq6++et2mPeYyR1xCHWqEeBARHx/xAH2w3nrrlbXXXrvGSXvOVeJtb3tb3ceaPhL2MdKsvPLK1aAC2sGntfval1e84hVVDKPdt91buulMTJSL6bwinOL0spe9rGoc+aGl2zC0i0PRcssEhIZCZKih+f0YTlhxxRWrAFVAW2Zh5TPco4clg7397W+vPi+GLojlAw44oA6FwDU++clPls9+9rM1E8rYXfSK+X8S4cTRnnvuWQXRu971rjqMbiioX1SjhaX9V1gcy6fnsY99bN32oQ99qPa4VQKGToRTeBUMQ/biqQOw1157lQMPPLAK9TD+vPjFL64dGUNa3Hkg3T37Liq7VlE1/F5uueVqxeRcz1u+8OxUlCqulgdCCGE6QtASQeo6vrnQRqtD+bCOZODhl2vkjgVWWw0WR23lTjvtVEfgtIVGYQcZYg/77LNPDTM9AkYSukW6sJqOJpAZzLQXjuunXZtm0f40v3/p3EQmTUSE0zf9bdZUI5za1re85S31eTdXE2EfhnZxaASygtIykOEKllUZ0VBDS2iJrnCxECtwG220UVl33XXLYostVi3HemqEj0zmGsz+RCv/HRl5NOd2hd81iB2CaI011qgPnW/RG9/4xuo/NBLCI/PzqXKssBFN66+/fhXbXDde+cpX1krhda97XXUdIZg5rYuTODjWvVnNR3PpCPcMLhN8w3WC+I2/4x3vqHmiizzA2m+ShzzUxbOSNw2TyVcqMtZnHw1Dq+RCCGE6wkD16Ec/uhqsTjvttOpvbIRX2zaapZBxisGquRVAe81izIpsFI9LY9d1bZAQL2E79NBDa/tNY7SOgDaB2x3jC72x0korVRHc7yMs3RjHdAJMfO1ihHq33XarVml+2vRHgyHvsssuK9tvv3116/B9EJEO3FC4nHIToXlM2hyWhQqGZuyXyGClY23l4kBIsuxK+DYc4xgZVKFrvU7mfc7/hDCBKVMbImeNPe644+pEP0MbMmo/HqxjTMIiovSE//nPf1aLrsy6xBJL1MyvYhgNGYTwJqCIsDZcZPhJGFo4n/CEJ9RjFSBh9LFfoVIIxXXQeofTCf5QJmF61oQua0B3MqXnwiLCJ6wfz0meMnGPj7nRCh2fkUYWQghhOqK9XHPNNev8CyKZcUi9OJJhx7HacG6H6t4uRui0u0Qno4SR1kGEZmCkI+S//OUvVyHbOgOMZlwjdRS+/vWv1//NGNeFjuBe0R2VbGhXPvKRj1TXhJe+9KV3a/9pnic/+cl1sYDPfe5zA+da0UU6SRd5wypTJiPSXf2j9YPI0Ahk4lFm5GbBEkyUmrzH8msfCGQPw5BDw0PwaceALzM/Uz03D0rPbaQhID6pZl8SwYYIzMZ1HoHO34cF2gS80SyE7smd4q1vfWvtPa222mrVEg6+yApHO7dZr1s4xYs/F0u5XqiJY1kebmLwLFRG0tyoA/cZw2Hd3r5KSmeMhaQfz0wnjK+dwu+5yput4xZCCNMdbS+LsdFVKyw85znPmTUa2g+jD0OCEdWG4wzDMywYpdthhx2qMNTOdtv0QYVbSFtq0qR+orUte+c/AwqDVxcjw9oL4rEf6UFY0gi0h5Hrhn22+899g8voeCzvNhE04yODIh1kSVbPflDD22UoBLKMQGwQuoa49aSWX3756vupJ9pwnGNkxmb903PTmzNJjo+ODOfBKHhEsWFwAthDbGK1YT8xzjXCciV6unp6MrxCS7ATwPZ1wwHXk3lb5uhHZiHIWjhZlB1rxQP/3Vtlw5JpyF8Yw8Sgh2/ptgbXFpVZswZ4/nr5r371q+vvLu35+s+6LP8ZJmzbfPrzVQghTBeaiGP80aZpI7WNbVUp+/rrQPOEbOtOeGZpNlneSF1DO9muPai0NsBCAuKt7T7jjDPqChM+RhOtRMGAwuj15z//uR4PhhcGOuvkj0Rrg3QYmp82pAd90aBD2rGDhHC29IFOEw1ndKEb/kFl4AUygctnhW+nGa8WE+eXxNJH8LYMxwqo12abJWJYf61iwSlcj/S1r31tFcasv/x1WKI33XTTmjlZConotrpEg++vzM2twkoTJtEZfresDSu067A28j3qPmzX0lPUG3aMRcT7cV9hYHEk0EzKY2EmisVHWAxViX+YWOQtfmSG9b72ta/VYT0TR9qwFXGsA6RT1cVsbZ0jS/l4Zp4pX3MNg8qeD55hNRV+fwcqhBCmA9plbagXLWlriUEjq4bTrVqgzdQOttWkwCBhWTKCsot5ONwGvDdA28jCqj6d15dJTBTqc1ZQS9jRJ83CTRzTCgxo4tvcS+gRo9Xmp0gnopFRzEilJeK6OMdkP37Y3FDa+sEN7ZW2xfsZHDeobQujprh6dwSrMYh8hiYeAP3xGkQG/k16hmJkGL0vvSgCub05xdAEkcLqyg1BYWNVZi3m2+tcbgksekStTMkaaEiCmDEcwhotU7su/2bntd6u3jDfXxZp1zSJy9D5xhtvXJ3u+Q0LiwLclmcBseS+4uR4w+9t5YqGAi/celjiYf/mm29ee6HCqEfp2ioZ1swwOvf0TXo6QtJdZ0ReI4xNfGhv/uFm49osI11LCOu/0YTmssPK75nKN0YeXI9LBtcMFQLr8tyggsmb9OaMBloZzpv0Jp68SW/6oOOuDrunb9IjgNRv2iz1n/pK2wjtszpSu8zfWPtKBFvC1EpTrY4FC6j9/msT1cWMRnyR57bu7Ge836SnI0Coqt+1OeJPf3DVs50+oAm0C9oD6cCIRoc4VlpIA+2EEeJuu2Ib8Ug7KGO0Sff5aFdoGW2Ca2l/pPF4QnTf0zfpab+86EQ4aTc6CvQXvSOPCH837nODvKuD0PTgRLDAzIc2pXZuE94UCP47IcwLrLhGC4wSjFcF2HBtPuSWApxskaqRMElDRWK1lDAyno3O8KCulzqdsISXuRvmROj4heHFqKU1962U0G/JnUi88Y311KToyWLQdAbxb01j1nYGt0GjTRAkarfccsve1sFC3uWSw5tAh30iGAof5BCmCrOTVRIsASGEEOYdllRLnLZ5GvMr7c2r/S+dCoNFBHIIs8FQWVYQCSGEew7LJIvk/C4MuV9YCYvbZhhcIpBDmA0WsSeSB3GGcAghDBN8jM3vmN/n1XAJ8G6E8fYdDuNLWv0QZoNJlPM6iSCEEML/w9AwyEu2TRbSIe3K4BOBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOAyGQ73Of+/S+hTD33Ote96p5aMEFF+xtmT6I173vfe/erzAS0id1yOSgjEnrBRZYoLclDCsLLbTQfPMsxTN1xNiRJ6TXILc96iJ5eCJZYMZMet+nhI9//OPl+9//fll99dXLXXfd1dsawthQSP785z+XH/zgB2WFFVYoyy67bLnjjjt6e4eb22+/vZx11lll8cUXL6utttq0idd44vl/5zvfKbfeemt5yUte0tsaJgKN0WWXXVYuvfTS8vznP7/my9TZwwnhc8EFF9S6U7lZeOGFyxRLgQmD2Dv77LOrISU6Y2xoa7Q9iy22WHnuc587cG2Pev8Pf/hD/ey6665lpZVW6u0ZXwZCIJ988sk1gtO1gIaJQ6V33XXXlV/84hdVHD/2sY8td955Z2/vcKNSuvDCC2sltdxyy02beI0nnv9PfvKTctttt5VVVlmltzVMBBqlq666qvzud78rz3jGM8qDH/zgiI0hRWfnkksuKddee20tN6yF01kgX3TRRfX/yiuvHJ0xBrQ12p5FF120LL/88gPX9qiLrrnmmvLvf/+77LHHHuWZz3xmb8/4MuUCea+99iqLLLJI2WabbXpbQpg7rrjiinLUUUeVddddtzz72c/ubR1+br755rLvvvuWZZZZpmy88ca9raGfww47rPzrX/8qO+64Y29LmCjOPffccsYZZ5S3vvWtZckll+xtDcPIl7/85ToasMMOO5QHPOABva3TkwMOOKB2pqMzxgaDwz777FPL+GabbdbbOlj86le/KkcccUR57WtfO2Ht/kD4IBseDWFe0bslJqejC8Itt9xSK6swOuoP6RQmHmVMWYvlePhRryg384NFVR0RnTF25Al5Y5DTTF3EDXEiySoWIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEIaaGTNm9L6FEOaWBRZYoPcthP9HvToMeWMiwxiBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNBhqATynXfeWX7zm9+Uiy66qFx66aXlhhtu6O2ZPG699dZy9dVXl9/97nflqquuKr/97W/r/+uvv753RBhGvHf+uuuuKz/+8Y/LT3/60/rdtn5uvvnmcsopp5QLLrig/Oc//ylXXnll/dxyyy29I/4f+VP+kF/kmxBCGHbuuOOOcs0119R6769//Wv93eWuu+6q7aPP3//+997Wu6MdP+qoo+p+daSPazkX//73v8sf/vCHWXWw+tX13PPPf/5zuf322+v2QeBf//rXLD1wxRVXlMsvv7z+//3vf19uvPHG8s9//rPG1zH2icOc2gP7jz/++PLrX/+6t+W/SIfLLrus/O1vf+ttGVw8I3GVLp5no7WL0kjaDTJDI5CJ4m233ba8973vLUceeWT9v9dee5U//elPvSMmB5XBscceW3baaaf6OeCAA2pY3va2t5W999570sMT7jme6ec+97my5557VuH76U9/urz//e+vBbsflfNnPvOZWvGprHx/5zvfWb761a/eraHQYTrooIPKdtttV77zne/0toYQwnCzwAILlJ/97Ge1/dtjjz2q2Onyox/9qLz73e8u++yzT/nHP/7R23p3vvSlL5Uf/OAHVSB/8IMfrNe55JJLyr3u9V9J8rWvfa3suuuu1bgAYusb3/hG2Wabbcp3v/vdGoZB4bbbbivHHXdcTQ/twDnnnFPFrd/CSvjTBh/96EfLSSedVA4//PCqF77whS9Uo99I/OQnPylHH330/whpaf2Od7yjfOtb3+ptGWzEVzp84hOf6G35r0A+9NBDy8EHH1w7D4PMUAhk1uLdd9+9ipdNN920fOADHygrr7xyLaST3QO5//3vXx772MdW8fTLX/6yvPGNb6wCSQEmlk444YTekWFY+P73v187Peuuu255wxveUF75ylfWQtxfubNunH/++eU+97lPed7znlce8pCHlPvd737VKvCVr3ylWpQbKnaVJEv0ox/96HLf+963tyeEEIaXBRdcsLaBrIKnnXZabQcbLL5f/vKX6zZt4pOe9KTenv+HcYGIfNWrXlWWXHLJ8shHPrKKyIc//OG9I0q9rpE8I3p44AMfWBZbbLEqGJ/2tKeVhRZaqG4fBLQDwsY4ttpqq5UNN9ywbL755mWRRRapHYBHPepRtc0w+qhtIfIf9rCHlUMOOaRqm5E4++yzy+Mf//iaPg3pqa1ilSWgB33U+t73vndZbrnlahyNun7729+u21ucHvrQh5bFF1+8fh9UhkIgf/azn61DOs95znPKOuusUwvUZpttVnuYElhBJWj0RroiRc/ONhmJde+mm26qx3VFtQLXznN8O8Y2H7/7USBkfqJHJibW11prrWpRlHmd57v/KgPCql3Ldx9hsK/bg3RfQyej9SrDxKAAq3yWXXbZ8oAHPKC85CUvqb39/srdM1PIiWPPHzpMq6yySs2fhowgT6nYH/GIR9S86pohhDBdUP899alPLUsttVS1BGvfQOheeOGF5VnPetao9d7pp59eRfYaa6xRj3nBC14wqz0E1wpt4IMe9KDyi1/8om7TfmsbCVCia9AQVnEh+ohlIvAjH/lI1QWEom32aw98bKcD+l0o8Mc//rF2DrRDD37wg3tbS7n22mvr8RtvvHF12ei33A8iOj1LL710NRIZ+W/6TLtJRw264WjgBbKCw1Iskz3zmc/sbS21B6tgKWh6ZC9+8YvLhz/84dpD22GHHapoJlhYeF/3utfVDHXggQeWl770pbWHJ3MqkISQwszczyq8xRZb1My7//7716GMrbfeunfHu6On3D6uRRBDhvY5+uijyyte8Ypq+SaM3/Wud9Xrfv3rX6/DQ8L6oQ99qMbvL3/5S7VCu5+hGOFrFUOYeFZYYYWaFzxznSm9fRVcfwUvP6m8PdcGYf3c5z63WgROPvnkuo3VWAWnAeh22EIIYTpAwC666KJlpZVWKr/61a9muUJ885vfrCK2K+z6cYy6sRkZiGztuDYa3/ve96r4XnXVVWvbD65tLLTuN6jQAc24ddhhh1VRz0hie/Olbmgj6ICuhbjxwx/+sLZB/R0BI5U6Iptsskm99kjietCQHkQwlxujCl/84hd7e/6roQadgRfIhigkssw0UqGz7TGPeUy1/nK92H777avP56mnnlqtu0sssUTtvejJPP3pT69D4nq53DX0yPR+ZcbHPe5x5YlPfGIVRQsvvHB5z3veU3uArMOzg5BV4E888cTyjGc8owpwGAYi6olv91xxxRVrXAw/GWpRKQiPnieRLrMbcuH7utFGG2VIfhJhAeYTpmLWOeEu0To8DXmQD9wTnvCEmk8aCrln9cIXvrD6m+nwyBMqxWc/+9n/c50QQhh2tMfaXIJVe8kgwFhwxhlnVFe17nyMLhdffHEV045pEJHa3zYCx32A0YLQ1mZydSOQGTEGVSDzndaun3XWWdXH2JwWI8IN6WU/6zABrI152cteVnVBF2lKk+ggMAI2nKt90c4Y6bRfWmpvBh1tIePmy1/+8tqGGm2luYaBgRfIChoRIoMRnCNhnw/rn4fBX4nrRTvPpx1HDMnMfGJYjPVi27HtGAVdged4r+czEo5zr3333bdO7mKxfv3rX1+t2o3uvQ0pKPAqAYWDD5X4sB4b4iekhVuv/DWvec3dRFiYWFgv3vKWt1Qf8mWWWaY+T50VlVVDz53/cbdibzhOZSffGD4888wzqyuQZz8MveQQQphb1Hvc0Bh6GKVMUNOWMg41S2o/Jm1p2wjiRjNesZCaqEcUuy6XSm0slw0GJKN0jGGDSNMa2nlpwHDX2n5o68XPKOWOO+5YBSJt0a9pGFe4aYp710hG25x33nnVgEe3MLrpSBCbg45nSGfxyxYPEzTlnTYhc5AZ+BDKbBJSIis4DQWwO8NTZjTz1aoSMteLXvSiuwmcBouyoQs9XYLHcHnXyuc6emuswgrmaCgQhNURRxxR3TJYo03KakNCXdqxhowMx+tFKQgyuaEWcVGg/GfZFg+9wzB5eO7LL7987fCst9561RVGZd2QXxRyrjz9eG7ylBELk/0s76O3TDCHEMJ0RLumbX7+859f3R8s22bi3WgT6BgZWEfXXHPNu1kQ1b1PfvKTq6VYu0s889klholi8z7422o7BxVpoT2XFq9+9avrSDZf4wYtworK9YJrpbaFG2Z/R8JqXeKuw9CFOJbWRLHVLwhNHy5/gw7tBh0jk+AZkVjRm4vNIDPwAllm4Y7QrLoNAtIwhmGXViCJFJnINhZd3xU+ny78lAlagpsLBSt1O0ZGJ1Yt3SaTN7+oLu26jjW8xOLL8qiXq4fcjkG7rkzCKV0GcV/DJbZx6neMysFvw/yWRVFQwuRgZnDr2LAAsOZ7fjpK8Jw9V5MmPO9+HOvZsRrr+HCt8Exb5dfyQAghTBfUe9pOwtXopzaMEai1j/20yXkMWP37tfGso4xHBHKzwHJBYMhiKR1kgdzQVsCIItcRiIeP9kCbsvrqq1cDHmNKd6IdNxLtvlHu7ooezjO/hSHO3CWf973vfVVzOH6Q3fha2wjP3jwsnR7+yPYNOoMfwplstdVWtQCee+651WJrOMcas5ZU0yuV6UyGInYJUNa+Y445pmYs231a5jRhTgFVkAka212jZTLH8OshYj1YFsV+LPjtOizYP//5z2tmNhHQfSxPw/+57SfUFRqivflQySR8kRyjl6m3qGfdlsvRKTDzM0wO1pTkViH9DV/pvKiwfUA8swqP5F6hoyU/ePYENFeN1772tXWfPGTmdf9ycSGEMMzwryXu1G9cAbgX7rzzztVFUPvJsqlubOIILMFELvHbj/aOz63zCL9mYTavhxsiscmYNKio6/lWm9/Uj/Qg8KWHEWO86U1vqoLRWtG2w2RHbQUDS4N2ML+JzugaZ6Q5CyzhPMirWbRVvVi74RlvsMEGVc91PQAGlaEQyJbVsrqDoW9DDDKFzGIymx4sNww9Nv69a6+9dh3iID5Z88wSJXQIVQ9EpjQUQhARyQq6Hh1fIEKH/5Tt1mlkWew6ysN13dNQigl53mrjmoaN+NiwYivkhpwIcYLb8IpzGsLn2HZtq26waqtAHEeIDXJlMN3wHFXQhvf4h0t7/mEmd8LESs+16zcH+UVlrzJXQZpwaUUV12pDYCZVqPTkvxBCGHa0Z4QgFwhGH8YBo6g+RnMJPe2otre5qVn2klGI5XSkCegEkzZVm941DhnNY1DyGVSkhY6A8Btx7p84Z782hQ5pPsPSZ8stt6xahCunNGUpl2bdiXvaENc0t0lHoRnyGGyau6j9g+jOJ6x0EMHv5TENeUDchX/QWWBmD2VKZxF5Gx5TO7eCOUFkKJCsvkSJQmXoollpFU4ixTEyTBvWkHltd5zfMqtjbXeszOl6wuE8223zWy+t2+MlYIlqx7i++xoy8Nv1ZQqC2XH2207AE1BEODcL57hv6wWCkFYYbBMWn5EqkvC/qJC9/Y7ldl6G4eQJz7TlIxZ8eQt699ad1InhV9zF8W10guVEZdeQfzxPecjH/v4JGXNCnrCSipUzLFcYRsa8A40St6gwsXiBAQNF6wiG4cWSW0bNLEXav6Tl7FDftTZWO6pua26OUO81gxBDlrrU5DTGJIaprvtAF2XYNV1PGwrtJwOD9ntu688uc6Mz5hZtPsNZ0xtNX0B7oo1ooll733QLg53zxFX7462rXoSmo9GQHtLT8dA2ubb01z6Ik/NpFN/HC2HjysEoxLVjXpAWbTk7Yesa/YRfuLk0zivyrhVDtM/cUiaCobAgNySmt9LouSpkMpsCKOG7M0cVJr9tdxw3BsfaZqimZV4PzTmO8V/BdA7By3roXl1xDOe2Y1zPf7iWjO83EeyavrufjCAMzmuZxXWbOIbvelSOcZ2I48nD8/HMWPT14Js4BncZz8aoQj/yo2fs2XbFMXRwPHv7PdN7UrmHEMKgoL4k1LRx6s2uOIZ96j0fdSnLJ19ZVlDnjAaR7lzXb2grtbODXH/SIOLary+gvddO2O5DYzSxq413Di3Aimw762oX8W5awqdd23Va++IZSKdBw3NsYdcGdhH+eyKOJ4uhEsghTDbNbWcYCnMIIQwa5nUw/nCXCP8LSzBfXS9P6ReSYWqJQA5hNuyxxx51kmi/lSSEEMKc4YO633771aXcwv9i9HGXXXYpb3/723tbwqAQgRzCbGjDYSGEEOae1KFzRholnQaPCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIocNACOSFF1649y2EuWfBBRcs97vf/cpCCy3U2zJ9WGSRRcp973vf3q8wEuoP6RQmnnvf+961rN3rXrGtDDv3uc99arlZYIEFelumL6kj5g55Qjkf5LZHuy8Pz5gxo7dl/Flg5sUn7upj4GMf+1j5whe+UJZZZpkJjWiYnmiob7zxxvL73/++POpRjyqLL754ueuuu3p7h5s777yzXHHFFeX+979/WWqppaZNvMYTFfmVV15Z7rjjjvKEJzyhtzVMBMra3/72t/LXv/61PO5xj6v5MnX2cOJZXn311eWmm24qyy677LQ0LjTUEepR/8U1eXbOaGukmU7F0ksvPXBtj/x77bXX1jpo7733Ls94xjN6e8aXKRfIH//4x8vll19eXvOa10QAhLlGxX7VVVeV008/vTznOc8pyy+/fLn99tt7e4cXlfmtt95aTjjhhLLEEkuUl7/85dMiXuMNK8LXv/71cvPNN5cNNtigtzVMBKw1P/rRj8pFF11UXvnKV9YOqU5cGD48yzPPPLMaFpQbQmi6Ckd16Ve+8pUqqqIzxoa2Rtvz8Ic/vKy11loD1/Zo9wl49dE222xTVl555d6e8WXKBfJee+1VC+t2223X2xLC3PHrX/+6HH744WX99dcvq622Wm/r8EP06UCyemy22Wa9raGfgw46qPzrX/8qu+66a29LmCi+/e1vl1NPPbW84x3vqKMaYXg57rjjyqWXXlp22WWX8oAHPKC3dXqy77771s50dMbYYJwxus96/MY3vrG3dbC45JJLypFHHlk23HDDssoqq/S2ji8D4UhmeDSEeUUfTx6ajpYB8YqVbvZIo9Qhk4MyJq2nq7VxfqI9y/kBdWjqiLlDeg1y26MOmujwZaZFCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCGGuuOuuu8pf/vKX+gkhhBCmI0MjkO+8885y+umnlw996EPlrW99a9luu+3KvvvuW6666qreESGEeeGf//xn2X///csHP/jB8qlPfarcfPPNvT0jc9NNN5U99tij/OIXvyi/+93vykc+8pH6u1sWzzrrrPL+97+/HHLIIeX666/vbQ0hzK/ccMMN5Zhjjinbb799edvb3lY+/vGPl0svvbS3N0xHPv3pT9d2Ze+99571rP3fa6+9yq677lp+/OMflxkzZtTtg8hQCORbb7217LLLLuWjH/1o+fvf/15e+9rXlgc+8IHl8MMPL5dddlnvqBDCvPCgBz2ofk455ZTyqEc9qiyyyCK9PSOjUvv1r39dlltuufLYxz623H777eWII44oX/ziF8u///3vesyTn/zkKqDve9/7lsUWW6xuCyHMn+hUE0pXXHFFedOb3lRe97rXlXPOOaf8/Oc/7x0RpiOrrLJKbVcuvPDC8sQnPrFue8hDHlJ++ctfVkOM9mOBBRao2weRoRDIRx55ZDnzzDPLgx/84CqSX/rSl5atttqqvOQlLyn3vve9e0f9P90eie8j/e5ug2Hj/m0hzA+ooB7/+MeXhRZaqCyzzDK9rSNjJOdb3/pWrfiIaec8/OEPLw996EPLN7/5zfKzn/2sHqcSfMQjHlEe85jH1N8hhPkXQviCCy6obffTn/708qIXvaiOBKtDwvRlxRVXLBtttFG59tpry29+85u67corrywLL7xw2XzzzWvbMcgMhUDWA9GIv/jFL66WY2h4DzzwwLL66qvX3yByjzrqqPLJT36y3HLLLXUbaxe3jM9//vPVunX11VdX877GHIZ/v/KVr1ThbfsZZ5xRbrvttrovhPkJZWxOvXl+xz/60Y/KOuus09vy3xGeV73qVeUJT3hCLZM33njjmK4VQpg/YMgymkQk/+tf/yoLLrhgec1rXlNe8IIX9I4I05XNNtusPm/uNYyQjJ3LL798eeYzn9k7YnAZeIHMP9LwzL3uda+y1FJL9bb+F9t8Go79zGc+U77+9a/PGrpZfPHFy69+9avy4Q9/uDbsTPqGeZZeeul6XduPP/74st5669XerGM0+CGE/0XH8mEPe1h53vOe19vy346pcrbJJpuUP/zhD7X82RaBHELASiutVNZYY43qhsXVgmsk16zUEdMfo4lveMMbqrbii0x3MagMAwMvkK+77rpZjS2zPP74xz/WCXsmAumNcP6H38961rOqpfiiiy6q2/RcH/3oR5cHPOAB5bDDDiv/+Mc/yqKLLlp/86M87bTTyrrrrlue9rSn1Z7Ou971rnL/+9+/nhtC+H/uuOOOWu7WXnvt3pb/x4jNmmuuWYWzTqqRmpHcn0II8x8siDvttFPZdttty+WXX14F07HHHltFcpjeMGIacbzf/e5XTjjhhLLqqqv+j7FzUBl4gczvGERymw1v5jzLr0J28MEH1yFdcI/YeuutyyMf+chy8cUX1218JlmNNeosySeffHItrArmn/70p/rQHK+Bd91rrrmmDgGFML/D1ag7mnL++efXzuhaa63V2/L/KJ8wO91Q6kEHHRSf/hDCLNQLb3zjG6sLJB/kAw44oHzve9/r7Q3TGUZJz5wwJpCHhYEXyCb/EMkaYMO34L/CUsWqzPpLAF9yySXVskwYexiELqdwViwWZStfGObho2wljIbr6uH85z//qRZmS89kWaowvzHSUCdBfPbZZ/d+lfK1r32tliGT70aCIDbJb8MNN6wz1H//+99nCDWEUP7617/W+Qva28c97nFl9913ryO1P/3pT3tHhOmMdoAWo7VM7B4WBl4gg3+wJUG+//3vl7/97W/VYkwMS/RmufrqV79a1l9//WoN5utkvxn13DI8FC4VW265ZbWA/fa3v60Pqy1RxXLMT4ZwNtuSwA5hfqJZe5sbk1EUZcqoC4hd5UkZ6xe9fne38UW2BJwGsTtHIIQwf8Ll8dBDD63tK7hrGd0drbMdphfaF8/cf899WBiK1suaidtss02dhGd5tx133LH6OOqBapjNjLXSxX3uc59qxmd1JpBZsfgls4QRwUz7L3vZy6pI9rCe8pSn1KVGLFvFP0ovl5AOYX5CeeAbpoNoBGXnnXcu73jHO6q/sfWRoYwsscQSdfSmC39C5Ywvf1sIXrlUXhEfwxACq+G5555b65Y999yz7LDDDuW5z31unbcQpj9G9k866aQ6OfMb3/jG0KwUtsBMRT+ljoKWVmNlIlBnhwTlYqEHqtG1fh7/SCtPOJ+1ihWYBVlD/+c//7mKXS89IKwd54UFJukRwoZ5WMu4VngDmGv5zU9qySWXHKphgPkdVk5v7OFGo9KdLhg18ZY6y6fx3ZsolCdrUypjbUTGf51PPmOWVtx0003rGqbCwYe/YTRHZ5VVwMowbfTFb5Wh5RjbPIKJgi8ji/d73/ve3pYwUXC5MY9DB8jzDsOLFSW8sIG7w0Qbhrg5cnvUfqtXtLVGcBmzJoOx6ozwX+gh87zopC222KK3dd7htspoSW5qDyyc0G1H5gV518viNt5447ou/0QwNOOfrMPLLrtstQI///nPL0960pOqNcuSUwqZVSiIYIWPeF5hhRWqPySr11Of+tRZb/MiolmO21CySXr2W9Da9vbChBDmF7gbKU8W8FdufJSHZzzjGbXcfOc736lWZqMz/ZUaQazsKYtd1yTHcbOYaHEcQhh8jCrp6K+22mq1DVe3TJY4DlOPdkT7op1ggLyn4niyiINgCGG2fPe7360V26C/9SiEEEIYLyKQQwijwlXi1a9+dXnnO9856y2WIYQQwnQnAjmEMCqGwrwSlL9gCCGEML8QgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDhHIIYQQQgghdIhADiGEEEIIoUMEcgghhBBCCB0ikEMIIYQQQugQgRxCCCGEEEKHCOQQQgghhBA6RCCHEEIIIYTQIQI5hBBCCCGEDgMhkO973/v2voUw9yy44IJlkUUWKQsttFBvy/Rh4YUXLve5z316v8JIqD+kU5h4lDFl7V73im1l2Ln3ve9dy80CCyzQ2zJ9SR0xd8gTyvkgtz3afXl4xowZvS3jzwIzLz5xVx8DH//4x8uJJ55Ynv70p09oRMP0REN9/fXXl1//+tdl6aWXLo961KPKnXfe2ds73Nxxxx3l5z//eVl00UXLk570pGkTr/HE8//lL39Zbr/99rLCCiv0toaJQIP0xz/+sVx99dXlqU99as2Xd911V29vGCY8y8svv7z885//LMsvv3wVQtO1/SX21KP+R2eMDW3NxRdfXB7wgAeUpzzlKQPX9qj3//rXv9b6Z8899ywrrrhib8/4MhAC+Sc/+UlZc801U9mGuUZF/6c//al85zvfKSuvvHItzMTSsKMyv/XWW8u3vvWt8ohHPKK86EUvmhbxGm88/9NOO62m1TrrrNPbGiYC1hpCw2eNNdao+TKdtuHEszzvvPNq3bn22mtXa+F0FsinnHJK/b/WWmtFZ4wBxpmTTjqpLL744mX11VcfuLbHSNaVV15ZO3k77rhjWWmllXp7xpcpF8h77bVXHfrYdttte1tCmDsUkiOOOKKst956ZdVVV+1tHX5uvvnmsvfee5dll122bLLJJr2toZ9DDjmk/Otf/yo777xzb0uYKHREdUi23nrrstRSS/W2hmHkS1/6Urn00kvLTjvtVC2F05n999+/dqajM8bGbbfdVrXZkksuWTbffPPe1sFC3j3yyCPLBhtsUFZZZZXe1vFlIBzJPIwQ5hUWAXloOlqzxCuW49kjjVKHTA7KmLSertbG+QlWwvml3KhDU0eMHeXbqJw8Mqho9yc6fJlpEUIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNBhaATyXXfdVf785z+Xb37zm+Vzn/tc+fKXv1wuueSScvvtt/eOGAxOPfXUsvHGG5df/OIX5Uc/+lE55ZRT6rbvfOc7vSP+yx/+8Idyxhln1H2nnXZa+de//tXbMzl8+tOfLm984xtn3ffGG28sF154YTn++OPLMcccU84+++xyww031H0hhBBCCPMTQyGQ77zzznLUUUeVddddt/7/1a9+VQ477LCy++67l6uuuqp31NRDbJ555pnl3ve+d3nkIx9ZfvCDH5T3vve9ZYcddigf+MAHyhVXXNE7slQh+o53vKPsuOOO5Utf+tKkCv1bbrmlfO1rXysPfvCDywMe8IDa0dhss83KzjvvXIU9wb711luX733ve70zQgghhBDmH4ZCILOyfuITnyiLL754Ofjgg8vHP/7xst1225VHP/rRZaGFFuodNfX8+te/rlbYF7zgBeVhD3tYecUrXlEWXXTRKpj//e9/V6ssrrzyyvLLX/6yhp34X2eddcqDHvSgum8yOP3008v1119fXvOa15T//Oc/5bjjjisXX3xxee1rX1v23HPPsvfee5fnPOc5ZeGFF+6dMTnMmDGj9y2EEEIIYeoYCoF89NFHlwUXXLCKtiWWWKJue/GLX1x222238qhHPar+BiHNgtu45pprykknnVS3f+tb3yrnnHNO+etf/1r+9Kc/lW984xv1WC4bLKZ+/+Y3v6kWVOdwf3C88whfAvIrX/lKFbZE7Uj8+Mc/rmJ4pZVWqr+b4HvCE55Qbr755mpRBost9wVWZq4jCyywQP00fvvb35avf/3r1aUExLWwCCNXDWH+7ne/W+NiG+H9z3/+sx4Lx5588sm9X/8LgfzQhz60rLrqquWOO+4o1113XRXrhPu1115bOx6Esni0NPrZz35Ww3rRRRfV63MfcQ9xcg3ncSe5/PLLy+9///safulqG0t0c9fwTOxzjbbNOY776le/Wv+7TwghhBDCVDHwAvnvf/97FYoE8hOf+MTe1lLuf//7VyHXrJxcLbgyfPCDH5zlV0uMfexjH6v+ttwy7CP8fvjDH5ZDDz20irx3vvOdVejxaT7rrLOqACa8TzjhhHL11VdXscwq/P3vf7+6HThHWPohuonqVVZZpTz1qU/tbf0vLMnEMkHr3j/96U/LMsssU5ZddtkqLruw6B555JE1XN/+9rfrNvc74ogjyrbbblvD9JOf/KQcfvjhVZTuscce1SebAAdf4l133bW6dhCq/UgHcXzVq15Vxfz97ne/svLKK9d9hPN73vOemg4ENKv2BRdcUO974oknVuEqXYhY1/7Qhz5U9/GnluYHHXRQ+eMf/1gFPncNaep+H/3oR+vnpptuqpZr4TvkkEPqsxMX95QunvVHPvKRgfMrDyGEEML8xcAL5GYZZWHlLzsafGqf+9znVutus9Sy0C699NLl6U9/ehXPz3zmM6tFdLnlliv77LNPdW1wTZZUwnmNNdaoxxKHrNUbbbRR9c1dc801q+X64Q9/eFlqqaXqtfthfSYan/3sZ5f73Oc+va3/tSKvsMIKZckll6zikPgl5glpIr/fWkr0XnbZZeUpT3lK/S8+hKT7EqzcIITpXe96V/0tfoQ29xMQ6eJJVJ9//vl1WxedAQKUaAfL8atf/eqy6aablvve977V6vv+97+/fP7zny+33npr2Wabber1//a3v1VL7yKLLFLe/OY31zQTL8+HP/hiiy1WnvSkJ5WnPe1pNd19pMX2229fxbj7snRLx/ZxP77Y7rPFFluUt73tbWWvvfYaKLeZEEIIIcx/DLxAZuUkjgnN2267rbf17th+6aWXVhGMNrmsuS+wJLN6+s/vluAjhIlP1yUYCVCuEH77cAFgBWURJT7bsSPB6sv66hpEej8E7ktf+tLqKiFsRCarbX98hPfnP/95edaznlVFOUtvm4TY7v3Zz362+mM7RridI2xNaOsAsOoSz6zeXbg0cJFwb2K/oUNgsqBOwvOf//zyj3/8o1rYuZbwodZRYOk98MADyyMe8YhqIRcXov9FL3pRdffQKbnXve41K52Ep1mCV1tttfKQhzykxg32O1aHQadCujcfbPcfyUIfQgghhDBZDLxAZmlkkSW4uBc0DOkTr7YTgsTfeeedVwUxH1/47kPM8R/mqsFaOhYBxjJLhI7Fmsnqe+6551aLKQHZj2u87GUvq+IRBKbrt98QTkKbpdV/cbXqxe9+97veEf89hmsGa654+91wD/EWR+kgjs4VtgaLMveH9dZbr7pWgIglUglWopx7ifBJTwIZa621VhX17svqjiaC3/rWt1ZxS1CP1oFo4exO+rOtCXv3DiGEEEIYFAZemRDHLJDEFIFnOB78ZPkU81tlHV577bXLM57xjOomQciZVEY0Oo+l8w1veEMVhVwHusJ0JAg9/s2vf/3ry+Mf//jq6sCSjSb2WHH51DqWBdW9WD9HQxgIT64H3CuEoQlK/32IYi4LLLbEtvDy4YX7OsbkRCt5EJXtfBDEJiOyVEsH6cFCy7e3QTgT8Nw3Gu4nHU2cAys4dwnC1Uoc4Aoi3KzJXRcTcXjMYx5T3TNM8COoRxK7hDvRL04N12dVdg/+2/aDBbzfLzuEEKYKcyzMGwkhzF8MhenOhDXikp8v31v+wyZ5sSITgNwriE4WX59mTSamrfnrOCsycC1gbSauYTs3BxbmBvcCwpM7BneIz3zmM/X6rkXUscp+4QtfqGLdb9e3ygPLLr/cLtwO7Od7y9eZEDWxTTisiuEeLLPNAm5Sm+uI64orrlit5+L3l7/8ZZaANAmvCVdhMjlPHPgHC5PzpIVOhWObu4k4uCdLdvNXRour9aX333//Gj7Hve51r6u+zHB9aUUQ+w+dA9ZpYdCR4H/cXEaEich1XatsePEI6zS/bukhLs4jpnVoNEDEvY4OH+Q5dWCmAu4ufK91Bkz6nJ8w+rL55pvXF8u86U1vqp1N/22TJkZPwpxRH0g7HWCr4yh7RsGshy5fmciqTglzh7T0cib1UFtTXh1inXxpbcKyelT6qtdMbGY8wAEHHFDP5ZZmBaORsOwlFzowvnA1Mw/kla98Zdlkk01q/e25mRDuWlz92pr3JjV7tp67yd4hhOFhKAQyqyfLr/WPl19++WqtVdHttNNOddjeC0QINqKMpZeIftzjHldXjWBJJY6Jtre//e11/WSVIzFnmxUVHvvYx1ZhDJWrRp+fMqvoC1/4wlkT5NyPqHOMipGFl9WU28Lqq69ez29o/Fhit9pqq/pCDufxe+ajzBrsI9y77LJLnTRoqTVWZgKXeBRHrg0sxjoGznv3u99d79VwDz7VhKxwrL/++rVhkA6EqAly9okvH2LWdtdp1nAIm4Zkgw02qGEi0D/5yU/W1SRYjOE893n5y18+y83FfUzSk47CSvy/5S1vqc9DXE26s+qIuHhuXpTivkS146SXa7kui7i4cPXQGeqGb1BgdZdPpEVzM5lf8Fx0IgkNIkQeVMY8K4JBBy7MGeXfSIy8rh5T3ozA2K7jra4aaQQmzB4jd+oxBgGGAfWHETVilVBlNGG80Ik3GmjehLoZjjFKx+jgOfTjuTAY6OC7PpFtG8OJjzbEb8+SaNaRVo+bVwEGAO2F+zF8hBCGiJmV9ZQyUzzNmNlD7/0aLu66664Zu+2224yZwnHGTDHe2zp4zBSlM2aK0hlve9vb6vfpxsxGb8bMzsOM888/v7dl/JnZIaj5dGanZcbMzlhv68Tyn//8p+avo446qrdlajj88MNnfP3rX58xs+M14+yzz54xs5M14+c///mMmZ2fGraTTjqpd+TU8IlPfGLGhz/84d6vwWVmZ3LGzI7kjJkd8BkzOxa9rTNmHHfccTNmirwZf/jDH3pbBpezzjprxnbbbTdjpijsbRkMPv3pT8+YKYJnXHrppb0tM2acfvrpM9Zbb72a7jjllFNqOl944YX1N2644Ya67cADD+xtuTv77rvvjI022qh+n9kxnDGzY1/LQ+Occ86pZQH/+Mc/Zqy44oozjjzyyPobMwX0jE033XTG7rvvXsvzIPGFL3xhxq677jpp9dlUMsw6Yyq45ZZbap7t5vVB4xe/+MWMbbfddsYFF1zQ2zL+xFxxD2B15n/MQtFdFWLQaO4VLCdWrAhhbjAaYLSDVW5mnVG3GVI2P4DbxfxmUR8PWjqife9uC3OHeRcsx21isVE0rm1G4LojUtK4P51HS/fmHmeZShgxNJJofXqjesqA6/dbnvMcQ5geRCDfAww7c7XwGWQe+MAHVn/RkZagCyFMHtyRTEr1AiIv3+Hfzf0p3DO4qVkZiD+wOQ4mHzMKdDtv3CCIVwLXuvnS3uRkYnokzFWx7yUveUn9zQjCPYzfOBejL37xi7N8mRtczyxn6bqu7xlzQxrLykkhhMEiAvkewNfMyy2e/OQn97YMJqwr/K/5O4YQpp42V8AnFsd7DuuulxRZbcJEYiN76mdzUboQySy/Le09B9tGwsRhE4vbGu38w01yNpmZ1dgEP3MvzB/p4nl2r5/nG8JwEoEcwj1A42iiTghjgWgy6dfk1A033LBOejSxLNxzuLqxHpv8a2ULa953IVSJYRZhk7ylvecw0qRgrho+Jud197MEm/hMGG+99dZ1tSRuGA0jBCaFe+Op6xtdfNSjHlWFcghhuIhADmEeIXa82ZCPdwhjRb5hxWxY5SDccyyfaTUKyzB6YZIViLqMZikeCUtOWgu/rUYBnWHuGWCxtvIPC7WVMjxTEOFdMezZdp91CGF4iEAOYYy04VhWIngZDQtSW/95fsDEJSIgVvO5h1CSh4imJqggTREhdc+wLCU3iwsuuKAu/eYFR12ku3kj/dZcVufu87Ccm2uwNFs+rmHZUC+Iaq/MJ8L5OlsCUp3g+Skb3Q5P6wx1rx9CGA4ikEMYA14iYNKORtKi/6xHXgigMe1viKcr1j/+3Oc+V308vVjGmtBh7BBdhuONOLQX+HAH8KIh+YjlM/6q9wwvSWpr43exVreXfUhnLxMhbHHYYYdVgexlN20kyLPR6eWy0V2XWjnXmbEevlfsW0OfiG6T+Ihn53nGVrnAV7/61foSJ9fUoQ4hDA8LzKyQp7RG9uY0lZBKJ4R5wUL/xAW/v4laqYMVqFmGWpHxn08iH8W5Gb4dK6y0XthimNdyalNNNw3Ed6LiPbeYLEW0e5HJIMNy2SyJ8k2zOnbT1NJ5gwzxd/LJJ5dtttmmrhoxaBColt+04kRX3Cqr0tn/bt51fP+23XbbrT4r+ckKQI12DYLaC5AIZq4W7T7da3m2tnvezWJt2yCtZmEVDi828aIob3qdzkRnzB3y94c//OHqQmSZz0FE3j388MPry350jCeCobEgq5gsh2SJHfgvgfT6/SeSLrnkktpQeluS7SZZ2OdNR60RCmFeULne9773rR8WKh+vCSdoNIjzA900mJ/iPV4QRy39mptOf5qGe4Y09LZC6dpFXrWvP+/2b9NeaEesGd8Vx2jX4Hbh7a5EZfc+3Wu17Z5ze76DJI5DCHNmaATyj3/84zrjeL/99qs9dVYj78j3qmazhY8++uiy5ZZbVhHttcbW/TWU5jXG++67b4aDQwghzJarrrqqWs3yWugQwtAIZL5c1htmDbbQvuV39txzz7rkjp7+tttuW4f9HvvYx9ZtSyyxRF3UnZ+YoffpPoQUQgjhnsHveMcdd6ztSAhh/mYoBDLr77XXXlsFsJnDXCjWWGONWok1vzKfjTbaqApj32+44YZyxBFH1Akwyy67bJ3hHEIIIYwG1wkvVOp30QghzH8MRS1wxhlnVP8tQtnsY29Lmh1tooTJESMt6xNCCCGEEMJoDIVAPu2006rF2Cs/n/jEJ9aF2U3Ga7QJF/CdQOZ2wQ95s802q9bn7vEhhBBCCCGMxsALZG8uuv7668s666xTRTL/YqtTXHjhhXW/pbC4U5i4B8sm3XTTTVUQ//73vy/nnHNOOfHEE+sxIYQQQgghzImBFsgswXyOLbnjNZ+sw/zDiGVuEwSwNyd5370F9x3PJ5kfmUl8hLTzVlhhhf9ZsieEEEIIIYSRGGiBTBC/7nWvqytUEMYWZffCBEu7vfjFL67b2u9nP/vZ9XirVbzjHe8o2223XXWxePvb316vkUl6IYQQQghhLAy8i4W3G/mYpEcA+27x9fZWovbdB46xULvfbdH2LNAeQgghhBDGylBM0gshhBBCCGGyiEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOAyGQF1hggd63EOYe+ad9phvTNV7jSdJocklaTx/ml2eZOmLuGYY0m+jwLTBjJr3vU8Jee+1VbrvttvLud7+73Hnnnb2tIYyNe9/73uXSSy8tRx11VFl33XXLC17wgnLrrbf29g4vCv5//vOfsu+++5ZlllmmvOlNb5oW8RpvFlpoofKpT32q/Pvf/y477rhjb2uYCBZeeOFy+umnlzPOOKO89a1vLY9//OPLHXfc0dsbhgnP8uijjy6XXXZZLTcPeMADyhRLgQnjXve6V9l///3LggsuGJ0xBrQ92pp99tmnLLnkkmXLLbccuLZHu3/xxReXY489trzhDW8oq6yySm/P+DLlAvljH/tYfRAPfOADe1tCGDsKsw7Wv/71r3K/+92vVvzTpaIXjxtuuKFWBtO5AbsneP433nhjueuuu8qDHvSg3tYwEUjrm2++uX7U1/Jl8uRw4lmqM2+//fZabvyezqgjsOiii9b/Yfa0tocBQlkftHIuv950003lyU9+cjnkkEPKCius0NszvgyEBfm+971v7dmFMC9cfvnl5fDDDy/rr79+WXXVVXtbhx9CRPlYdtlly6abbtrbGvo5+OCDa2O/yy679LaEieI73/lOOfXUU8vb3/72stRSS/W2hmHk+OOPr6NvO++8c+2AT2f222+/WRbkMGdYjD/+8Y+XpZdeumy++ea9rYOFvHvEEUeUDTfccMIsyAPhg6wXG8K8wnooD03HoTPxyjD27JFGqUMmB2VMWsdyPPy0Zzk/oA5NHTF3SK9Bbnu0+xPd5mcVixBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhBBCCCF0iEAOIYQQQgihQwRyCCGEEEIIHSKQQwghhBBC6BCBHEIIIYQQQocI5BBCCCGEEDpEIIcQQgghhNAhAjmEEEIIIYQOEcghhDDF3H777eWGG27o/QohhDDVDLxAvv7668uZZ55ZP2eccUa58MILe3sGkyuvvLKccsop5eyzzy6nnnpq+eY3v1lOOumk/2vvPmCkKN84jj/HUS0IdgW7WBFREWLX2I1RoxgTEhO7scbEFkv0LDEWNBrFaOy9YdREE02MYsOCYgELloAFO8ZYQJDy9/uwc47n+ReU82aX7yfZcDc7OzO7t/O+v3nmnSGeeOKJePXVV2tzSWoUM2fOjNdeey0ee+yxGD9+fPzyyy+1Z+Yj+LL/P/nkk/HJJ5/Upv5u7ty58fjjj8fo0aNj9uzZ8fLLL2fbMWbMmNbQTNtB+8cyPv3005wmSVX23HPPZbv19NNPx+eff57Tvvzyy3jqqacyG7XXHlZJ5QPyvHnz4pFHHonTTz89LrjggtYPuap+/PHHuOmmm+Kkk07Kf19//fX8kpxxxhkxatSo2lySGkVzc3O8//77cd5558WZZ54ZU6ZMqT3ze/ilPbjjjjuiS5c/N7mzZs3KtmL69OnRtWvXePPNN7O9o91g2aBdOeecc+LWW2/N3yWp6shrZJ+rr7462zb8/PPPcd1118Xtt98eP/30U06rqsoH5GWXXTY222yz7ER69uwZe+yxR+2Zatp0001jvfXWi++//z423HDDOP7447Oz23PPPaN79+61uSQ1Chr+jTbaKPr3759nkN5+++3aM/Ory/fff3/u+6uvvnrO09a4cePyTNnw4cPz94EDB8aSSy6ZbclSSy2V03bYYYfo0aNHrLXWWrHaaqvlNEmqsgMPPDC23XbbPPjv1q1bTmM4Ge3aoYcemu1mldXFGGQ+WCovPPj5iy++iHvvvTduu+22+Oijj2pzRZbxmc6QhuI052effZYVaKZzxHLnnXfm6U7MmTMnJkyYkNUbnuP0KH88UPnhFCfL4mewLk6DUgn6f6c5i22lQ6Ojowp02GGHxdlnnx1fffVVbgOnSjl6+u677+Lhhx/O07MTJ06Mu+++O5+nU73rrrtyu1gvwzZ4D6yb983vH374YZ6KLaY/8MADracs+JdlFe/7mWeeiRkzZsTXX3+d67vvvvtyOp9N8V5Y3j333JPL5zMGVawbbrgh56WyxYPt4sF8rKPqVX2po3Gma/3114+111479zUCL956662smBB6i2pwWw8++GBsueWWscoqq+TvzNerV68/zU97wkOS6gE56Nhjj40ffvghMwrIX2uuuWbsvPPO+XuV1UVApvMpo2IzduzYePTRR1vDK5h+zTXXxAcffJDVZqywwgrx7LPP5qlJOiA6K/5QvI5wd+6558Zyyy2XYZVQSmAFAfuiiy6KG2+8MZeHpZdeOv+4rLc4XfBXmpqacplUlDjFQBCn8sN0xiueeuqp8cILL2SFnA6VCjljD59//vkMsldddVV2sgTU9957L0MsQzQ4QOjbt28GXE67Tp48OafzGfH6o446KiZNmpRHaARhtpV13HzzzXH++efndrPMK6+8MlZaaaUM5qeddlq+xyWWWCLfHwcGVLwIxpwaoRLO+yDUM0aS0yNsD9NZR/H5SIsr2hPC61ZbbZX7K+PswP63++675/7Uth3D1KlT44033oj999+/NmU+lkf7QTtEO8CDfa+9ZUhSVVE02GuvvbKA+dBDD2Vm2XvvvVszWpXVRUAuo4OgukKHw9FJ+UMmCBIui9OSoNMilFIt3njjjWO//fbL8YBUSAmWVHaYNmLEiCz59+7dO1/34osvZvWX+Qi0ICCDkPp3lRyCKAGYdRFcCbPgdcsss0z+TkAnkLMegvyQIUPiuOOOy6MrjrjWXXfdOOaYY3K7Ca+8N75s2223XZx88slZsaLKxGnczTffPIefTJs2LatWfD48x2fEl5F5Cd90unxmHChw2pb3Tof+7rvv5nYxP++PeRhIz/YNGjQot4tOnM+SMM/2Dh48OMdcVv00idTR2C8IswTkPn365L5G+KXt2HfffXMfbQ9nqGi3hg4dWpsyf1k8OFt11lln5dhmDm7ZdyWpnpAnDj744Lzg+JJLLokNNtgg80o9qLuAXKADIcy19VfTCJdcTUmwJNhRAWUa44VB6F5jjTUyWIJK6oknnpjBtAjIRcfF4+8wVGOXXXbJYQ877rhjLh8EdSrJO+20UwZZQiihn21kzCFhGPzOvHyRCMzFtJdeeimr3nS4bBt4PZ0nR2aEeEJ/8fnwHMMtGNrBeyUEg+cIvwyr6NevXwZoKlTF+6OCRWBnLDVfbqrEjH9km/iMPv744zjllFNyyMbyyy+fy5QWZ+w/66yzTu7DnBViuBLj7wjA7VV+2cdok6iulM9IFfOy311++eUxcuTIuOyyy1r3XUmqJyuvvHLsuuuuWVgjF9WLug3IbdHZtFV0NEXgI1QWnRUVVEIi1Waqrtdee22OEaaSyphaLrShQyI0EwYJmO2NIaRT/CvMT5i84oor8ktBKGedVJq4aI8KLkMfqFIzfUHwHtjmonLO63gvF198cVbEDzrooAy7oNMlNNPJrrjiilnt5T0V28zQD8YRUxnmNcX4a1Al5mDi6KOPzmo2Q0IYelFU5NkOfi6Cv6T5B8Z0BOzrnE7cZ5992g3HIERTVaEtaE/R3rAflwO0JNUT2jLOzpMZymf4q66uAjLBjA+afwmGPCjfc1ul4v7IPEdnQqdE5ZeOitcQDDnVyalK7inKeGQ6My7iYwwyIZXpBGgugKMKxBAJgiWBmXGCrKtYL+th2czTFs+VwzlVV8YUFxVpsNwDDjggO0huBcc8haJj5LWFYhrVppaWlpyfqjHzMCaZaVSrbrnlljy1C4LwgAEDct2cqqW6BV7Dg+kcANCRM2ayGLbCg+1n6MXhhx+eBw+EcKrXzMPnRrWbqhYVaw4epMVZsb+zz2299dZ5twrOuDBOHxygtw3KXGDLWZr2zsCwf7c96C+3EZKkjlX5gMxYXYIr/xLEuOCOsMawAYIrY/0IalxAxsVpVDupAnP3BiqqvJahBAwFIMxyxTiVYoIhVV1eT0AkVDIWmLDN2D/G+Z5wwglZ3WF4AfNxNwmWw7xUfy699NIcIlHG/VC5GwUhkoBOhZgKMtvD8gm1PM/2sw6qyFyAU1Rv6QRZD9PKd4egEkyYZju4MI4LCFk+nwnhnueoBFOd5pQs87OdBF8OAgqsh+l8TryXI444Irf5+uuvzwvxmJ/gT1WdW9RxRw2CMgcUhGJey3OEev4WVKW5+4e0uCL4sg+xT9AG4cgjj8wzMBxs8hwP2hH2HbD/c0cYLuArX8/A/s/ZK85a0U5wJgcsm/38nXfeiW+++SanSVI9IFNwLRbtGre1bFssqKrmFkqPnYjQSjVzm222qU35I4IfnQq3QSKgUaanOsMpfsbU0qFQlSVsUmWlakN1lqDIRW7Mw2uopPI8AXX77bfPeyvz4A9FUGSIAdvA0AUqsoz7ZT2se9VVV83nGU7Ac1woR6WI9bIs7m9a4ItA5Yfgy+u5/x+/Dxs2LKcx3pfAzvbwOoI64ZP3x8U9dIjffvttroPqE/PQybIdvBfWyTLZnmKsMfPyOxf6UNEliLMeTmVssskmuR1UycGBBiGZC+9YN58p74ttYH4q6FSaeR0/E8DZpt122y0PKPh7MI6Iz4QQz3r4DNj2zsLnxcECFwuW/xb1ju8YByH87Rg3r/ZxZoPvKN/DzkBbw4El+x3tD/sbbQ/7FO0LnQLtBvsobRMVY+5CQ+A95JBD8nUF9m2msw+yHPZR9k9CMz8Xy2ff7AwceBP0ac86c5/Xv8edlej72G+Ka28a1d/lDP0RuYq+h3ZrUVxQx/eMa744M8/ds+in/+2wMZZJcY6sQg7pCE2/NeCdGuW5qpEAyBhX6Z+gwk0FnP9ooZEaQBqUCy+8MA+mCFJqH7cs5MCXM0P1gEDN7Ri54wWV5noaX8x/oc+tIRkuVlw8rPrEvew5S8Hwu3oaF/pPmDMWDgVI/udiDsgZZllFfHe5DS93ICvfBWhRapiL9CSpHnAfcs56MFbZi+8kqZoMyJL0H2LIDPc3Ly6alSRVjwFZkv5DjPvnbjSNflpbkuqZAVmS/kNcLFzctlGSVE0GZEmSJKnEgCxJkiSVGJAlSZKkEgOyJEmSVGJAliRJkkoMyJIkSVKJAVmSJEkqMSBLkiRJJQZkSZIkqcSALEmSJJUYkCVJkqQSA7IkSZJUYkCWJEmSSgzIkiRJUokBWZIkSSoxIEuSJEklBmRJkiSpxIAsSZIklRiQJUmSpBIDsiRJklRiQJYkSZJKDMiSJElSSSUCco8ePWo/SQuvubk5evXqFV27dq1NaRw9e/aM7t27135Te2g/+JzU8djH2Ne6dLG2Uu+6deuW+01TU1NtSuOyjVg4fCfYz6vc99Dv8x2eN29ebcqi1/Tbwjtu6QugpaUlRo8eHVtssUWHvlE1JjrqadOmxYQJE2LAgAHRv3//mDNnTu3Z+jZ79ux45ZVXom/fvjFw4MCGeV+LEn//8ePHx6xZs2Lo0KG1qeoIdEhTpkyJyZMnx+DBg6NPnz4xd+7c2rOqJxzoTJw4MdtO9huCUKP2v4S9cePGZVthzlgw9DX0Pb17945BgwZVru+hLZo6dWq2+yNHjowhQ4bUnlm0Oj0gT5o0KTu4mTNn1qZIC4eGjwb+119/bagQScPO+yKE8N7UPj4jPivbkI5HsOJBx2Q4rm9U32g7+Vs2emikgsx75L1qwfCZVb3v6devXwwbNiyDfEfo9IAsSZIkVYkDySRJkqQSA7IkSZJUYkCWJEmSSgzIkiRJUokBWZIkSSoxIEuSJEklBmRJkiSpxIAsSZIktYr4H7cT6pxCUGIAAAAAAElFTkSuQmCC\" height=\"560\" width=\"584\"\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate multinomial logistic regressions predicting the likelihood of sex trafficking of an adult victim, sex trafficking of a minor victim, or labor trafficking based on organized crime dimension.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eComparison Category - Adult Sex Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eComparison Category - Minor Sex Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSex Trafficking of a Minor Victim\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eLabor Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLabor Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSize\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003cp\u003e(0.169)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.427\u003c/p\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.516\u003c/p\u003e \u003cp\u003e(0.217)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eScope\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.705***\u003c/p\u003e \u003cp\u003e(0.149)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.793***\u003c/p\u003e \u003cp\u003e(0.212)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.499***\u003c/p\u003e \u003cp\u003e(0.188)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSophistication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.519***\u003c/p\u003e \u003cp\u003e(0.152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003cp\u003e(0.188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.681***\u003c/p\u003e \u003cp\u003e(0.157)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStructure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.275\u003c/p\u003e \u003cp\u003e(0.114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.066\u003c/p\u003e \u003cp\u003e(0.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003cp\u003e(0.118)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-Identification\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eName\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eFamily\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eStrength\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.466\u003c/p\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003cp\u003e-0.459\u003c/p\u003e \u003cp\u003e(0.365)\u003c/p\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003cp\u003e(0.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003cp\u003e(0.310)\u003c/p\u003e \u003cp\u003e1.873***\u003c/p\u003e \u003cp\u003e(0.380)\u003c/p\u003e \u003cp\u003e0.717***\u003c/p\u003e \u003cp\u003e(0.190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.022***\u003c/p\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003cp\u003e2.332***\u003c/p\u003e \u003cp\u003e(0.293)\u003c/p\u003e \u003cp\u003e0.762***\u003c/p\u003e \u003cp\u003e(0.155)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.01\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003cp\u003ep-values adjusted through Bonferroni correction\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate multinomial logistic regressions predicting the likelihood of sex trafficking of an adult victim, sex trafficking of a minor victim, or labor trafficking based on organized crime group type.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eComparison Category - Adult Sex Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eComparison Category - Minor Sex Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSex Trafficking of a Minor Victim\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eLabor Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLabor Trafficking\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMom \u0026amp; Pop\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.105\u003c/p\u003e \u003cp\u003e(0.282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.511***\u003c/p\u003e \u003cp\u003e(0.325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.616***\u003c/p\u003e \u003cp\u003e(0.253)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCrime Ring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003cp\u003e(0.211)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.005***\u003c/p\u003e \u003cp\u003e(0.544)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.445***\u003c/p\u003e \u003cp\u003e(0.522)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStreet Gang\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.517**\u003c/p\u003e \u003cp\u003e(0.529)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.136\u003c/p\u003e \u003cp\u003e(1.127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.653*\u003c/p\u003e \u003cp\u003e(1.016)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCartel/Mafia/Syndicate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003cp\u003e(0.639)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6.877\u003c/p\u003e \u003cp\u003e(20.390)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.381\u003c/p\u003e \u003cp\u003e(34.106)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIllegal Enterprise\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.681***\u003c/p\u003e \u003cp\u003e(0.286)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.777*\u003c/p\u003e \u003cp\u003e(0.296)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.457***\u003c/p\u003e \u003cp\u003e(0.291)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003cp\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.1, ** p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.05, *** p\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.01\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003cp\u003ep-values adjusted through Bonferroni correction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Human trafficking, typology, sex trafficking, labor trafficking, organized crime","lastPublishedDoi":"10.21203/rs.3.rs-6597507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6597507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite prevailing narratives that human trafficking is largely driven by transnational organized crime groups, little empirical research has rigorously tested this assumption. This study presents a novel 5-S typology\u0026mdash;size, scope, sophistication, structure, and self-identification\u0026mdash;which yields five different types of organized crime groups: mom \u0026amp; pop, crime rings, street gangs, illicit businesses, and cartels/mafias/syndicates. Analyzing over 2,390 federally prosecuted human trafficking cases in the United States from 2000 to 2022, we systematically assess the nexus of organized crime and human trafficking. Findings reveal that the majority of cases (67%) involve unorganized individuals, and among those involving organized crime, most are small-scale \"mom \u0026amp; pop\" operations or decentralized crime rings rather than sophisticated cartels or syndicates. While this may be a function of potential selection bias inherent in using prosecuted cases as the basis for empirical analysis, the results challenge dominant framings of human trafficking and suggest the need to recalibrate enforcement strategies and policy assumptions. The study concludes by discussing critical implications for research, practice, and the future study of organized crime and human trafficking.\u003c/p\u003e","manuscriptTitle":"Organized Crime and Human Trafficking in the United States","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 10:03:27","doi":"10.21203/rs.3.rs-6597507/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"162dce5f-d447-477b-a328-f92bd1837241","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-10T10:09:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 10:03:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6597507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6597507","identity":"rs-6597507","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}