A network approach helps us better specify and model collaboration among people involved in organized crime. The focus on collaboration raises the boundary specification problem: Where do criminal organizations start, where do they end, and who is involved? Traditional approaches sometimes assume the existence of simple, rigid structures when complexity and fluidity are the norms. A network approach embraces this complexity conceptually and provides methodological guidelines for clarifying boundaries. Boundary specification in organized crime helps solve four puzzles. First, social boundaries: a network approach reduces confusion about social boundaries as criminal entrepreneurs interact with criminals and noncriminals in diverse contexts, only some of them illicit. Second, boundaries of group membership: network data and methods obviate the need for formal membership attributions. Third, ethnic boundaries network analyses reveal that the effective boundaries of criminal organizations are based on social relations, not attributes such as ethnicity. Fourth, recruitment: attending to the larger social environments in which organizations are embedded provides a clearer view of how mechanisms of recruitment cross seemingly rigid boundaries between members and prospective members.

中文翻译：

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网络视角下的有组织犯罪中的合作与边界

网络方法可帮助我们更好地指定和建模参与有组织犯罪的人之间的协作。对协作的关注提出了边界规范问题：犯罪组织从哪里开始，他们在哪里结束以及涉及谁？当复杂性和流动性成为标准时，传统方法有时会假设存在简单，刚性的结构。网络方法从概念上包含了这种复杂性，并提供了用于澄清边界的方法论准则。有组织犯罪的边界规范有助于解决四个难题。首先，社会边界：网络方法减少了社会边界的混乱，因为犯罪企业家与犯罪分子和非犯罪分子在不同的环境中互动，其中只有一部分是非法的。第二，小组成员的界限：网络数据和方法消除了对正式成员资格归属的需要。第三，种族边界网络分析表明，犯罪组织的有效边界是建立在社会关系的基础上，而不是种族等属性。第四，招聘：关注组织所嵌入的更大的社会环境，可以更清楚地了解招聘机制如何跨越成员与准成员之间看似严格的界限。