This article applies social network analysis techniques to a case study of police corruption in order to produce findings which will assist in corruption prevention and investigation. Police corruption is commonly studied but rarely are sophisticated tools of analyse engaged to add rigour to the field of study. This article analyses the 'First Joke' a systemic and long lasting corruption network in the Queensland Police Force, a state police agency in Australia. It uses the data obtained from a commission of inquiry which exposed the network and develops hypotheses as to the nature of the networks structure based on existing literature into dark networks and criminal networks. These hypotheses are tested by entering the data into UCINET and analysing the outcomes through social network analysis measures of average path distance, centrality and density. The conclusions reached show that the network has characteristics not predicted by the literature. Key Words: police corruption, social network analysis 2 Public officials who place their own interests before those of the public have corrupted a system in which they are supposed to act as agents of the public will (Lauchs 2007). Police are an essential part of the Australian justice system and are the frontline actors in keeping the peace and social stability and cohesion. Thus good governance relies on honest policing. However, there will always be at least a small group of corrupt police officers, even though Australians are culturally averse to corruption (Khatri et al. 2006). Police officer's attract corruption because of their ability to enforce or ignore the law and police who are unethical or in financial stress are vulnerable to offers of illicit payments. Organised police corruption, which is a subset of organised crime, aggravates the situation because it threatens the community by undermining good governance. Organised police corruption constitutes "social behaviour, conducted in groups within organisations, that is powerful enough to override the officer's oath of office, personal conscience, departmental regulations and criminal laws." (Punch 2000) Organised corrupt policing is more dangerous than individual actions because collaboration between offenders can multiply their income; the income of the group is greater than the sum of the income of individuals acting apart (Morselli and Tremblay   2004 ). There are many historical examples of powerful organised crime syndicates of predatory police establishing themselves within the Australian police services. Policing bodies need to understand the nature and structure of these networks to be able to better identify and apprehend the targets of their investigations. As Warr has stated in relation to the policing of delinquents: "…it is difficult to imagine how investigators can develop, defend, or test general theories of delinquency without some knowledge of the organization and operation of delinquent groups" (Warr 1996) . The necessity of studying criminal networks is well established but has not received much attention from social network theoretical approach (Morselli and Tremblay 2004; Moran 2005, 62). The main contribution of this article is that in uncovering hidden (or confirming) bribe and other corrupt exchanges and their associated influence tentacles it provides a better understanding of the nature, structure and socialisation processes of these embedded networks. Understanding how corrupt police networks are structured and their dynamics affords better opportunities for strategies to be developed to interrupt dark networks and re-enforce positive policing practices. This study is a departure from current studies of criminal networks in that it draws on social network analysis to provide rigorous data to verify the characteristics of networks and particularly to uncover the hidden relationships that support them. This project will provide previously unavailable information on corrupt police networks in Australia. It is the first to study each of the separate inquiries into Australian police corruption and convert information from the inquiries into useful data for corruption prevention, detection or investigation; turn the unanalysed information and into actionable intelligence (Dean and Gottschalk 2007) . The project will provide insights 4 into the structure and dynamics of their operation by unpacking the topology of their interconnections and increase understanding of points of intervention and strategies to sure up or insulate 'good networks' and stop them tipping over the edge and to the 'dark side'. Although focused on the Queensland context, this article is part of a larger study that will interrogate corrupt police network across Australian jurisdictions. The article outlines and focuses on the first stage of the project being the corrupt police network in Queensland (Australia) called 'the Joke' that ran from the 1950s to the 1980s. Social networks form when people interact. Networks are a type of social organisation that rely on relationships of trust, mutuality and reciprocity, coupled with a set of common norms established and maintained through peer pressure, social approval and sanction (stigma), to bind individuals to a collective unit. The characteristic ability of networks to be inclusive, flexible in their operation and quick to respond to opportunities and problems networks can be leveraged to benefit individuals, groups or businesses or society at large (Jones, Hesterly and Borgatti, 1997). However, as Raab and Milward (2003) have noted networks can also have a dark side, where the network achievements come at the cost of other individuals, groups or societies. It has been argued that the particularism of networks, that is, the banding 5 together to pursue particular or common interests, is a key element of network disadvantage since it can lead to exclusivity rather than an inclusive approach (Taylor and Hoggett 1994). Such inclusivity renders networks as essentially private rather than public entities and therefore not exposed to wider levels of scrutiny or subject to external accountability regimes. Because of this, networks can be quite secret and invisible in their operation and endeavours. This opaque nature of networks and their lack of transparency, coupled with values and norms that support clandestine actions and goals, can provide a basis for corruption. Granovetter (1992, p.45) points out" networks can create their own norms at odds with the outside world to the point where they become a 'law unto themselves". In such a context, illegal activities can take on the aura of normality and members protect each other from the sanctions of the outside world. Most of the study on criminal networks has been based on the structure of organised crime syndicates. The primary contemporary document on this subject is the United National Office of Drugs and Crime (2002)  Network analysis is an empirical tool which can be used to identify, measure, visualise (map) and analyse the ties between people, groups and organisations (Scott 1991, p.113) (Bruinsma and Bernasco 2004, 90). These relationships can also be developed over time through empirical evidence that a non-family member is trustworthy. This is more likely to be seen in long standing "high end" organisations (CMC 2004, 4). It could be argued that a police agency is also a trust based organisation. Members build trust by working together in dangerous and even life-threatening circumstances that weed out the untrustworthy. Groups may even develop their own criteria for trust for example; the New South Wales CIB mantra was "you never trust a man that doesn't drink" (Padraic 2005, 19). Hypothesis 1: the network will only extend to those who can be trusted through association with a common denominator. Networks are made up of people performing specific roles. A key role is that of the broker who fills the spaces between nodes. Brokers are power players as they control communication between the parties that make up the network. In a corruption network it is assumed that the brokers will bring together the illicit operators outside the force with the police within the force who can provide them with protection. The illicit operators wanted support from the Joke, and that support worked because it was a syndicated operation rather than ad hoc arrangements between individuals. It is therefore likely that within the network are one or a few key persons who facilitate the communication between the payers and the police protectors. A police network will probably be different because it is a network within a network, that is, within the Queensland Police Force. It is highly likely that the structure of the QPF will influence the structure of the network as the protection supplied by the police officers is determined by their power and jurisdiction within this agency. Thus we should not see officers from unrelated sections of the force, such as homicide detectives, within the corruption network. It should be centred on the Licensing Branch which has jurisdiction over the offences committed by the illicit operators. In addition, the hierarchical rank of the officers should play some part in the network as their authority to exercise discretion over raids, charges and even internal investigations should make them attractive to the network. Thus just as a criminal network selects it membership by the skill sets that are required (UN 2002) the police network will, out of necessity, have to select membership from those who can protect the network. Similarly, the structure of the network will then, of necessity, have a pyramidal hierarchy reflecting that of the agency. Hypothesis 3: the structure of the corruption network will mirror the hierarchy of the police force thus it will have a high density. Hypothesis 4: The structure will be highly centralised reflecting the bureaucratic structure of the QPF. This will be reflected in long average path lengths as communication follows the chain of command and the network will have a high rating of centrality. Hypothesis 5: Social network analysis can identify key actors within the network that can be targeted to disrupt or close down the network's activity. The project followed three stages. First, data was extracted from police inquiries into corruption and the corrupt networks plotted as network maps. Then organised crime theory was used to examine the networks. Network analysis theories will be used to identify the strengths and weaknesses of the police networks to target strategies for detection, investigation and prevention. Data for networks should include as much as possible of the data set, in this case the corrupt network. It is difficult to obtain information on criminal networks and most information available is unreliable. Data gathered from informers and incarcerated gang members cannot be checked because researchers cannot know the true size of the people There are limitations to this study. First, the data sources are imperfect and rely on evidence produced at police inquiries and reminiscences of participants. Neither source of data is complete. Moreover, the latter can be highly unreliable. However, these are the best sources available. Secondly, network maps may plot relationships that have been identified by a third party without the benefit of confirmation. Thus the appearance of a name on a map may imply an unconfirmed relationship In view of this, network maps should be read cautiously and only in connection with the accompanying commentary in which the details of relationships can be expanded. In this way, as Rogers (1987) contends network analysis can serve to 'turbo charge' case study information. Given this article's specific focus on the Queensland policy corruption networks a content analysis of the Fitzgerald Inquiry (1989) report has been undertaken to distil three
Lauchs et al. REF apply social network simulation for the case of a real corrupt police network.
Corrupt police networks: uncovering hidden relationship patterns, functions and roles
Policing & Society
Sociology