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This paper seeks to identify ways in which governments and lawenforcement agencies might enhance the effectiveness of their efforts toanticipate organized crime. It starts by defining what is meant byanticipation, and differentiating it from the much more difficult task ofprediction. The analysis then identifies some of the methods and modelsthat are generally accepted as part of the existing knowledge base onorganized crime and highlights how these can be used to anticipate futuredevelopments and to develop warnings about how criminal organizationsmight evolve and behave in the future. The knowledge base includespolitical, economic, sociological, strategic, and composite models and showshow they provide a foundation for anticipating future developments inorganized crime. The models are either models about the kind ofenvironment in which organized crime flourishes or models about the waysin which organized crime behaves. What we do, in effect, is to identifyand elucidate `models' in ways that provide propositions about the kindsof developments, innovations or changes we might see in organized crime(both domestic and transnational) in the future. Underlying indicators provide warning about future manifestations of organized crime. Anticipating these manifestations provides a basis for appropriatepreventive, defensive or mitigating strategies. Finally, the article providessome examples of specific techniques of information collection andintelligence analysis that might assist in this task of anticipation. 相似文献
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Sleep sex may be a defense for alleged sexual assault. The International Classification of Sleep Disorders (ICSD3) states: “Disorders of arousal should not be diagnosed in the presence of alcohol intoxication… The former [alcohol blackouts] are exponentially more prevalent.” A panel member of ICSD3, quoting ICSD3 asserts: “alcohol intoxication should rule out a sleep-walking defense”. This implies extremely strong support for a prosecution hypothesis (Hp) over a defense hypothesis (Hd). I use Bayesian methodology to evaluate the evidential probity of alcohol intoxication. The likelihood ratio, LR, measures the amplification of prior odds of guilt, . By Bayes' theorem, . I use data from cross-sectional studies of sexual assault and prevalence of alcohol use, in college students, with data from longitudinal studies, and data from the epidemiology of parasomnias to evaluate LR (alcohol). LR ~1.5 or 5, depending whether alcohol does, or does not, increase the risk of parasomnias. The proposition of extremely strong support for Hp implies a LR ~1,000,000, so the proposition in ICSD3 is not supported by formal analysis. The statistical reasoning in ICSD3 is unclear. There appears to be inversion of the Bayesian conditional (confusing intoxication given assault, and assault given intoxication) and failure to evaluate alcohol intoxication in Hd. Similar statistical errors in R. v Sally Clark are discussed. The American Academy of Sleep Medicine should review the statistical methodology in ICSD3. 相似文献
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