“ Legitimate strengths in criminal networks ”

Extending from the organizing crime perspective, we study how legitimate world actors contribute to structuring a criminal network. This focus also underscores the facilitating role that some participants have in criminal settings. Based on a case study of an illegal drug importation network that was monitored by law-enforcement investigators over a two-year period, we find that although most legitimate actors (or non-traffickers) had nominal roles and contributed minimally to the criminal network’s structure, a minority of these actors were critical to the network in two ways: (1) they were active in bringing other participants (including traffickers) into the network; and (2) they were influential directors of relationships with both non-traffickers and traffickers. The presence of such influential participants from legitimate occupational settings illustrates how upperworld figures can facilitate criminal enterprise beyond the mere contributions of legitimate status and expertise. The presence of legitimate actors in criminal networks has been a consistent concern for criminologists studying criminal markets, organized crime, economic crime, and other forms of criminal enterprise. The overlap between legitimate and criminal settings is evident, but the presence of legitimate actors in criminal contexts is still ambiguous. Legitimate actors connected to networks designed for criminal ventures may serve as tokens or exploited prey, but they may also be consensual actors pursuing their own interests. Although their place in a criminal operation may be justified by the contribution of a legitimate status or facade to the network, they may also have a more active and critical involvement. Past research has provided opposing perspectives on this issue. The first follows a traditional organized crime framework and places the legitimate actor under the control of the criminal entrepreneur. The second follows an organizing crime framework that emphasizes the symbiotic relationships that emerge between actors from upperand underworlds. Our study applies social network analysis in weighing the traditional organized crime framework against its organizing crime alternative. Whether their functions are nominal or critical, legitimate actors are generally facilitators in criminal settings. We evaluate the contribution of legitimate actors in a case study of a hashish and cocaine importation network and highlight the various ways that nontraffickers contribute to the structuring of illegal drug trafficking operations. Our analysis illustrates that, at least for a minority of legitimate actors involved, their contribution as facilitators goes beyond the mere token role. 186 C. MORSELLI AND C. GIGUERE The criminal and legitimate enterprise overlap The threat discourse is at the forefront of the traditional understanding of interactions between participants in criminal and legitimate forms of enterprise. Members of criminal organizations are presented as the instigating and dominating force in such relationships (see Naylor, 1997; Woodiwiss, 2001; Van Duyne, 2004 for elaborations on the threat discourse). This perspective was most evident in early research on organized crime, which placed considerable attention on the increasing presence of criminal trade participants in legitimate industries. Organized crime members were perceived as outsiders who forced their way into legitimate economic sectors. Their methods of extortion were too formidable for the law-abiding legitimate entrepreneur to compete. The presence and progressive domination of organized crime members threatened the values and ethics of the free market economy. Indeed, this infiltration was perceived as a greater societal threat than the apparent domination of criminal organizations in prohibited markets (Cressey, 1969). More recent research has offered a similar overview of the legitimate/criminal overlap (see Jacobs, Friel & Radick, 1999; Jacobs & Peters, 2003 on labor racketeering in New York City). One alternative approach, the organizing perspective, counters this traditional and popular view of organized crime as a predatory force within legitimate enterprise and conventional society. Rather than presenting the legitimate side of the overlap as a target of organized crime members, this counter-argument centres on the symbiotic relationships that link legitimate and criminal actors in a common setting. Chambliss (1978) found such a symbiotic process in Seattle. He exposed a crime network that structured the vices and assured impunity through the alliances of criminal trade participants and a variety of legal actors: “Politicians, law-enforcement officials, professionals (especially lawyers, accountants, bankers, and realtors) and ‘legitimate’ businessmen became partners in the illegal industry” (p. 55). No formal organized crime unit was necessary to orchestrate the system and force compliance therein; the network was maintained by the contribution of all involved. The most explicit and complete assessment of the symbiotic relationship linking criminal and legitimate worlds was offered by Block and Chambliss (1981) in their explanation of union corruption in labor-management relations. They contested the term “labor racketeering” because it emphasized an image of criminal outsiders mixing with organized labor leaders to taint labor management. This image was problematic mainly because business actors were omitted from the racketeering framework. Block and Chambliss were also concerned with the growing trend that had “social scientists and popular “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 187 writers alike [focusing] on the ‘racketeers’ and the ‘rackets’, rather than the symbiosis between business and corrupt labor practices” (1981: p. 87). They proposed the concept of organizing crime, which emphasizes the historical process through which organized crime comes to be in a given setting. Unlike traditional theoretical frameworks of organized crime that stressed the domination of criminals who orchestrate legitimate spheres of society, the organizing crime framework inverted the direction of influence by emphasizing that organized crime is rooted in the legitimate sphere of society and that legitimate actors are critical throughout the process. Within the organizing crime framework, criminal and legitimate entrepreneurs are actors in the same political economy. Organized crime is directed by processes emerging from legitimate society. This may be observed in one of two ways: (1) in a political economy, criminal opportunities emerge in a consistent and increasingly organized fashion to progressively transform into a sustained organized crime phenomenon that combines actors from both legitimate and criminal spheres, or (2) members of existing criminal organizations may be solicited to provide their organizing services in legitimate settings. The first organizing crime scenario was documented in particular work settings, such as the maritime ports that Block studied (Block & Chambliss, 1981; Block, 1991). More recent illustrations include McIllwain’s (2004) study of New York City’s Chinatown at the turn of the twentieth century and two studies on human smuggling channels (Zhang & Chin, 2002; Kleemans & van de Bunt, 2003). These studies blur the traditional image of the criminal entrepreneur as a predatory force in legitimate circles. They also maintain that the organization of crime emerges from the abundant opportunities offered by consensual legitimate actors. The two studies on human smuggling also challenge the traditional image of the ruthless smuggler and exploited victim; researchers’ findings from interviews with both illegal immigrants and smugglers reveal that the former are clients and the latter are service providers. The second organizing crime scenario is most evident in research following the “Mafia as a private protection industry” thesis. Rather than extortion practices, the focus here is on protection services offered by criminal entrepreneurs in symbiotic settings throughout the world. In such exchange contexts, the legitimate actor is often the initiator of the relationship and the most likely to benefit (see Gambetta, 1993; Gambetta & Reuter, 1995; Milhaupt & West, 2000; Varese, 2001; Hill, 2003). The organizing crime perspective emphasizes the consensual relationships that unite participants from a variety of legitimate economic sectors with a range of criminal trade participants. Whereas much attention has been devoted to illustrating such an overlap in either legitimate industries and economic 188 C. MORSELLI AND C. GIGUERE sectors, or in practices that represent the overlap to begin with (e.g., corruption and collusion), we transpose this general outlook to study the presence of actors from legitimate sectors in criminal settings. Legitimate actors in criminal settings The presence of legitimate occupational actors is well documented in studies on illegal drug trafficking. Reuter and Haaga (1989), for example, described how opportunities to participate in illegal criminal ventures were widely available in legitimate work settings and how legitimate actors brought complimentary resources to criminal operations. Dorn et al. (1992) referred to such participants as “business sideliners” (see pp. 26–30) and presented them as a problematic subgroup in trafficking settings: “by virtue of their legitimate base, resources and channels and the hypothesized infrequency of their involvement, they are particularly hard to detect, contact or research” (p. 29). In such research, the contribution of legitimate actors to a trafficking network was restricted to their involvement in the circulation of a drug commodity, in which their legitimate status served as a useful front. Actors from legitimate professions and occupational settings also bring expertise and a variety of resources to a criminal network. This was a recurrent finding in a three-city (Turin, Barcelona, and Amsterdam) survey on ecstasy markets (Gruppo Abele, 2003). The Amsterdam segment of the research provided the most information on this matter. Overlaps with legitimate activities did consist of employees in legal companies who contributed to the distribution of the drug, such as “drivers for international trucking companies, luggage handlers, stewardesses and cleaners at the airport who can move easily on both sides of controlled areas” (p. 68), but also included links with chemists who provided laboratory equipment, chemicals, and contacts needed for drug production. Other examples of such resource allocation are offered by Lyman and Potter (2000) who illustrated the diversity and importance of legitimate actors in the context of illegal drug trafficking: “behind the scenes are many unseen workers: middlemen, financiers, smugglers, chemists, pilots, bankers, attorneys, and enforcers” (p. 223); “Indeed, without the surreptitious aid of public and private figures such as law enforcement officers, judges, prosecutors, mayors, bankers, attorneys, accountants, and elected and appointed political persons at all levels of government, the organized crime unit could not flourish” (p. 11). The presence of legitimate actors in criminal settings is well established. Much attention has centred on legal professionals such as lawyers and notaries who provide important services to criminal enterprises (Chevrier, 2004; Di Nicola & Zoffi, 2004; Lankhorst & Nelen, 2004; Middleton & Levi, 2004) “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 189 and finance agents who attend to money-management and investment necessities (Van Duyne & Levi, 2005). However, the legitimate actor is generally presented as a nominal supporter or passive service provider to the criminal entrepreneur. We can move beyond this pawn-like image of the legitimate actor in criminal enterprise. The term, facilitator, is generally used to represent participants in criminal activities who assist in supplying an illegal commodity or service; such participants are not necessarily from legitimate settings and consist mainly of labor and management available in any “irregular economy” to supplement operational needs in criminal trades (Ruggiero, 1996). Brokers in criminal trades, for example, are often described as participants who contribute to numerous criminal operations by using their social capital to facilitate the actions of suppliers and movers of prohibited commodities (Haller, 1990; Klerks, 2001; Kleemans & van de Bunt, 2003; Morselli, 2005). Aside from legitimate status, business experience, financial capital, and logistical resources, legitimate actors may also be well-positioned facilitators who offer similar brokering services in criminal networks. This is discussed by Williams (2001) who, in emphasizing the strategic positioning of legitimate actors in criminal networks, refers to them as “gatekeepers” or “crossovers”. The importance of such participants suggests that it is not because a legitimate actor is venturing in a criminal venture that his role or position remains, by definition, passive to the criminal trade actor. As participants, legitimate actors may be more actively involved in how the criminal venture is orchestrated. Our study pursues this line of inquiry within the legitimate/criminal symbiosis. We converge on how legitimate actors facilitate ventures in criminal enterprise by focusing on their contribution to network structuring. The following case study centres on non-traffickers in an illegal drug trafficking setting. Case study source and research design Our case study relies on electronic surveillance data gathered during a twoyear (1994–1996) tandem investigation (Project Caviar) conducted by the Montreal Police, the Royal Canadian Mounted Police, and law-enforcement agencies from various countries (i.e., England, Spain, Italy, Brazil, Paraguay, and Colombia). The Project Caviar operation targeted a series of hashish and cocaine distribution chains that were coordinated from Montreal and spanned across the aforementioned countries. The investigation resulted in twelve seizures: four hashish consignments and eight cocaine consignments. The principal data source comprised information submitted as evidence during the trials of 22 participants in the Caviar network. This evidence became publicly accessible after it was submitted in court. It included 4279 190 C. MORSELLI AND C. GIGUERE paragraphs (over 1000 pages) of electronically monitored telephone conversations between individuals intercepted in the surveillance net. We used these transcripts to create a social network matrix of the drug trafficking operation’s communication system during the investigation. Individuals falling in the surveillance net were not all participants in the trafficking operations. An initial extraction of all names appearing in the surveillance data led to the identification of 318 individuals. Within this pool, 208 individuals were not implicated in the trafficking operations. Most were simply named during the many transcripts of conversation, but never detected. Others who were detected had no clear participatory role within the network (e.g., family members or legitimate entrepreneurs who were not involved in any of the importations). The final network was composed of 110 participants. A binary, directional matrix was designed to keep track of ‘who-called-who’ within this network.2 The identities of all participants in the Caviar network are kept confidential and replaced by node designations (Node1, N2, . . . N110). After the matrix was created, participants were grouped either as traffickers or non-traffickers in the network. We began by identifying 82 traffickers (N1 to N82). They were involved in the planning, coordination, and physical movement of the illegal commodity. The remaining 28 participants were designated as the legitimate segment, or non-traffickers, in the network (N83 to N110). This second group consisted of individuals from legitimate occupational settings who contributed necessary resources to the operation, which included financial investments, money management, logistical and equipment supply, communication brokerage, and legitimate fronts. They did not have any direct involvement in the planning, coordination, and physical movement of drug consignments. In our analyses, we also distinguish between nontraffickers occupying roles as financial managers and investors (n = 8) and those occupying non-financial roles (n = 20). Can a participant in an illegal trafficking network be considered as legitimate or as a non-trafficker? From a legal standpoint, probably not, but we retain this label for analytical purposes. The labels, non-trafficker and legitimate actors, both refer to participants who occupied a place in the Caviar network because their presence extended from a legitimate occupation. The distinction is necessary in order to focus on actors from legitimate spheres who participate in criminal enterprises. The remaining participants in the network are referred to as traffickers or criminal actors because they represent the criminal labor force and management that are required in criminal enterprise. Although several of the traffickers may have had occupations in the legitimate labor force throughout the investigation, their place in the Caviar network was linked exclusively to their work in the trafficking operations and had no link with any legitimate setting. “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 191 After a general description of the Caviar network and its two main subsets, our analyses of the binary, directional matrix assess contributions of legitimate actors within the network in two ways. First, we examine the extent to which non-traffickers are represented among the seeds of the network. Our concern, here, is on who brought participants into the monitored criminal operation. Second, using reciprocity measures3, we assess how some non-traffickers directed communication within the network. Our final analysis examines the judicial outcomes of the Caviar case and evaluates how non-traffickers figured therein. Subsets in the criminal network A sociogram of the Caviar network is presented in Figure 1. Of the 110 nodes, 51 (46%) had direct contact with only one other node in the network. The 82 traffickers had, on average, 3.9 direct contacts in the overall network and 6.7 contacts if we exclude the set of one-contact nodes. Nontraffickers were less directly connected with an average of 3.1 contacts in Figure 1. The Caviar network. 192 C. MORSELLI AND C. GIGUERE the overall network and 4.5 contacts after removing the one-contact nodes. Within the non-trafficking segment of the network, those occupying financial roles had more direct contacts than those occupying non-financial roles. The Caviar network was concentrated around three key traffickers (N1, N3, and N12). The most accurate assessment of the Caviar network is that of an overlap between the networks of these three key participants. Although depicted by law-enforcement investigators as the mastermind of the overall network, N1, who was the most connected with 60 contacts, is more accurately described as the principal coordinator for the hashish consignments. N12, who had 28 contacts, was the principal coordinator for the cocaine consignments. Described by law-enforcement officials as N1’s “lieutenant”, N3, who had 27 contacts, was extensively involved in both the hashish and cocaine consignments. Whereas an important proportion (n = 29 or 27.1%) of the other 107 nodes in the network were not in direct contact with any of these three key traffickers, most were directly connected to at least one (n = 51 or 47.7%) or two (n = 23 or 21.5%) of them. Only 4 (3.7%) of the participants were directly connected to N1, N3, and N12. As a subset, the majority of non-traffickers were considerably dispersed among those nodes having either no direct contact with N1, N3, or N12 (39%, compared to 23% of traffickers) or who had direct contact with only one of the three (32%, compared to 53% of traffickers). For the remaining nontraffickers, their links to these key traffickers were slightly higher than for the remaining traffickers: 8 or 29%, compared to 24% in the trafficker group, were in direct contact with two or three of the key nodes. Most non-traffickers had minimal links with the core of the Caviar network. However, this does not imply that they were not providing facilitating services for the remainder of the trafficking segment. Indeed, Figure 2 shows that once all traffickers are excluded from the network, a disconnected subset of nontraffickers remains. Therefore, the principal contacts that non-traffickers had to the network were through traffickers, albeit not the three key ones. Although not cohesive as a subset, the non-traffickers did contribute to the seamlessness of the Caviar network. Once we removed all non-traffickers from the network, the single component was broken and 6 traffickers (N21, 38, 39, 40, 63, 73) became isolates. Their isolation resulted from the extraction of three non-traffickers who served as their only links with the trafficking operations: N87 (linked to 5 of the 6 isolates), N107 (linked to 2 of the 6), and N88 (linked to 1 of the 6). These basic analyses of the Caviar network highlight important distinctions within the subset of non-traffickers. Most non-traffickers do not appear to be critical, although a minority emerge as significant participants in structuring “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 193 Figure 2. Non-traffickers in the Caviar network. the network. Moreover, the contribution of these select few appears to be oriented more toward the trafficking segment of the network than toward other non-traffickers. Seeds in the network One way of assessing how some participants contribute to a criminal network is by studying how nodes are generated. For this analysis, we determined the entrance of each node into the network. Our concern here was on how established nodes brought new nodes into the network (see Table 1). If nontraffickers are primarily passive participants in the network, we would not expect them to be important contributors to the generation of new nodes. Our analyses illustrates otherwise. When we coded the origin of the 110 nodes that comprised the Caviar network,4 we identified a total of 21 seeds. The non-traffickers were well represented in this subset. Although they represented only a quarter of the overall network, they accounted for 38 percent (n = 8) of the network’s seeds. In all, they contributed to the entrance (or detection) of 20 percent (n = 22) of the nodes. The most interesting finding was that the majority of nodes generated by non-traffickers were traffickers (15 traffickers and 7 non-traffickers). The two principal seeds in the network were traffickers: N1, the main hashish coordinator, generated 44% of the network (n = 48); N12, the main cocaine coordinator, generated 12% of the network (n = 13). The third most important seed was N87, a financial investor who brought 9% (n = 10) of the nodes into the Caviar network. Non-traffickers occupying such financial roles were more important seeds than other non-traffickers. Six non-trafficking seeds were involved in the transport of money, as messengers, or as legitimate 194 C. MORSELLI AND C. GIGUERE Table 1. Node generation in the Caviar network Traffickers Non-traffickers Total Number (%) of nodes 82 (74.5) 28 (25.5) 110 Number (%) of seeds 13 (61.9) 8 (38.1) 21 Number (%) of nodes generated by 88 (80) 22 (20) 110 Number (%) of traffickers generated by 67 (81.7) 15 (18.3) 82 Number (%) of non-traffickers generated by 21 (75) 7 (25) 28 entrepreneurs and workers masking the various hashish and cocaine consignments. Only 2 of the non-trafficking seeds (N87 and N89) had operational roles as financial managers or investors, yet they were more important than all non-financial seeds in generating nodes: N87 and N89 brought 10 traffickers and 4 non-traffickers into the network, whereas the 6 non-traffickers occupying non-financial roles brought only 5 traffickers and 3 non-traffickers into the network. The direction of contact Assessing the importance of a selection of nodes in a network is also achieved by studying reciprocity (see Wasserman & Faust, 1994: pp. 510–511). A reciprocal relationship means that two actors are symmetrically linked in that they both contact each other. A non-reciprocal relationship means that two actors are asymmetrically linked in that only one initiates contact within the dyad. In asymmetric relationships, a node is either the director or receiver of contact. A relationship between a given node (A) and any of his/her direct contacts (B) may therefore be: reciprocal (A <-> B), directive (A -> B), or receptive (A <B). This relational categorization is applied to the Caviar network to identify the extent to which non-traffickers, compared to traffickers, are involved in reciprocal (symmetrical) or asymmetrical (directive or receptive) relationships within the network. The assumption underlying the “don’t call us, we’ll call you” dictum, which gains importance in criminal settings where the concealment of personal identity is fundamental, suggests that directors in asymmetric relationships are generally more important players. Participants who are more directive in their asymmetric relationships have greater control over how easily others can contact them. However, accepting this assumption means we are unable to assess whether some key players, in spite of their limited presence, can function effectively in the criminal network. In the overall Caviar network, the reciprocity patterns of non-traffickers were similar to those of traffickers. On average, traffickers maintained “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 195 reciprocal ties with 37 percent of their contacts compared to the non-traffickers whose reciprocal ties averaged 33 percent. The asymmetrical ties of traffickers represented 63 percent, of which 41 percent were directive and 59 percent were receptive. In comparison, the asymmetrical ties of non-traffickers represented 67 percent, of which 42 percent were directive and 58 percent receptive. Non-traffickers emerged as more directive participants than traffickers when we converged on the most connected nodes in the Caviar network. We restricted the focus here to traffickers and non-traffickers with 5 or more direct contacts (n = 14 for traffickers; n = 6 for non-traffickers). Traffickers in this select group maintained an equal proportion of reciprocal and non-reciprocal relationships (an average of 50 percent for both). This even split is also reflected in their non-reciprocal relationships, where directive and receptive ties both average 50 percent. Non-traffickers, for their part, had reciprocal relationships with 55 percent of their contacts and non-reciprocal relationships with 45 percent. However, in sharp contrast to the trafficking segment, nontraffickers were more directive in non-reciprocal relationships with 72 percent directive and 28 percent receptive. Non-traffickers who were involved in the financial aspects of the Caviar network had the greatest proportion of both non-reciprocal and directive relationships. Using reciprocity (or non-reciprocity) as a key indicator of criminal network positioning suggests that money managers and investors are as critical in orienting the network as are the main traffickers. The three most connected traffickers (N1, N3, and N12) all had networks that were evenly split between reciprocal and non-reciprocal relationships. Yet, only N1 had a higher proportion of non-reciprocal relationships that were also directive (79 percent); N3 and N12 had less directive ties (46 percent and 43 percent respectively). Of the six non-traffickers with five or more contacts, three (N85, N87, and N89) occupied financial roles. Only N85, who had the minimum 5 contacts, experienced more reciprocity. N89 had 9 contacts, 6 of which were non-reciprocal, with 4 of these non-reciprocal relationships directed by him. N87 was the most connected non-trafficker with 16 contacts, and just over half (n = 9) were non-reciprocal – all were directive. It may be that the high level of directive relationships within the nontrafficker subset took place mainly with other non-traffickers; if this were so, our finding would simply reveal that such participants were directive in the legitimate circles in which they likely occupied dominant roles. This was not the case. Recall that the non-trafficking segment of the Caviar network was highly disconnected (see Figure 2). If we consider the two main non-traffickers that emerged from this reciprocity analysis, N87 and N89, both were in contact with only two other non-traffickers; in all cases, these two main players were directing these relationships. This left 2 directed relationships for N89 and 7 196 C. MORSELLI AND C. GIGUERE directed relationships for N87 that involved traffickers. Even after we removed all other non-traffickers and assessed N87 and N89’s position among the subset of traffickers, their relationships were still largely non-reciprocal (54 percent for N87 compared to 56 percent in the overall network; and 57 percent for N89 compared to 67 percent in the overall network). The removal of nontraffickers from the network and the slight increase in reciprocity for N89 led to some change in N89’s non-reciprocal relationships: 50 percent of ties with traffickers were directive (down from 67 percent in the overall network). However, the removal of non-traffickers did not affect N87, who remained directive in all relationships with traffickers. Discrete participants and pawns A participant’s degree of implication and level of importance in the trafficking network can be partially ascertained by the judicial outcomes in the Caviar case. In all, 22 participants of the Caviar network were accused. Six were non-traffickers (N83, N86, N87, N88, N96 and N101). For the 14 who were found guilty and condemned to incarceration, the average prison sentence was 6.5 years. The most severe sentences were given to the principal coordinators of the hashish and cocaine consignments: N12 (15 years) and N1 (11 years). Our analysis was designed to identify those legitimate players who brought more than their mere status as legitimate actors to the drug importation network. The seed analysis identified the importance of the financial investor, N87, who was among the accused and who received one of the more severe sentences (8 years). N87 also emerged as a key player in the reciprocity analysis, as did N89 (another investor) who avoided arrest. Throughout the case, investigators centred much of their attention on an accountant, N85, who was arrested but not accused. Both N85 and N89 represented legitimate entrepreneurs who made important contributions to the operating of the criminal network (particularly in financial ways), but whose participation remained discrete. Their roles were suspected but knowledge about their degree of implication remained ambiguous throughout the investigation. We did identify these participants in our analyses, but they contributed little to the structuring of the network and their nondirective involvement kept their physical presence ambiguous as well. Other legitimate players served as legitimate guises for the criminal network. N83, N86, N88, N96, and N101 all had non-financial roles. N83, N86, and N88 were money carriers; N96 and N101 were legitimate importers who lent traffickers their services and company name. They were all under the direction of the main traffickers in the network. Their physical involvement “LEGITIMATE STRENGTHS IN CRIMINAL NETWORKS” 197 was detected, but they did not make significant contributions. They were the pawns of the criminal network, yet they cannot be considered as naı̈ve tokens. Their consensual implication in the minor aspects of the illegal trafficking setting exposed them to prosecution, albeit to a much lesser extent. Only two received prison sentences: N83 (31/2 years) and N101 (41/2 years). The remaining three were the only participants who were accused, but who were not convicted. Charges were dropped against N86 and both N88 and N96 received suspended sentences in exchange for their collaboration as informants.