Collaborative Research: Unintended Consequences of Law Enforcement Disruptions to Illicit Drug Networks

合作研究：执法中断对非法毒品网络的意外后果

• 批准号: 2145938
• 负责人: Osman Ozaltin
• 金额: $ 24.11万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145938&HistoricalAwards=false
• 关键词: Collaborative; Research; Unintended; Consequences; Law

The use of illicit substances remains an ongoing and widespread part of society, with the illegal drug market estimated to be one percent of total global trade. Although the true scale of this market is unknown because of its illicit, underground nature, the overarching US drug policy and strategy has consistently been to allocate large amounts of resources to law enforcement agencies to dismantle illicit distribution networks. The motivation for narcotics enforcement is that it imposes negative consequences on the supply side that both deter people from distributing illicit drugs and decrease the drugs’ availability to vulnerable consumers. Yet little evidence suggests the negative consequences disrupt the macro-level drug supply to an extent that alters the price of drugs, and very little is known about the meso level effects of these interdictions on violence in the broader community and drug consumers at risk of fatal overdose. Therefore, the purpose of this Disrupting Operations of Illicit Supply Networks (D-ISN) project is to utilize national integrated data to develop an understanding of the impact of law enforcement disruptions to the illicit drug supply on both public health (e.g., overdoses) and public safety (e.g., violent crime) outcomes. In order to understand the relationship between drug market disruptions and outcomes of interest, the study team will construct a county level dataset across 10 diverse states using three sources of administrative data: (1) National Incident-Based Reporting System (NIBRS), (2) National Center for Health Statistics (NCHS) detailed Multiple Cause of Death (MCOD) data, and (3) the US Census. NIBRS captures characteristics of crime incidents, including detailed information on drug seizures, crime offenses, and other incident characteristics in a nationally systematic way. The MCOD data will provide unsuppressed, county-level, mortality information based on death certificates and include information on cause, decedent demographics, month of death, and county urbanicity. Data from the Census will be used to calculate rates of drug seizures and control for county level population characteristics and resource deprivation. The county-level integrated dataset will include the date of overdoses (by type of drug), public safety events (e.g., murder/nonnegligent manslaughter, robbery, and aggravated assault), and the county where the outcomes occurred. The study team will employ methods of spatial temporal causal modeling, which allows for the modeling of causal relationships between time- and space-persistent features. Lastly, the integrated datasets will be shared with researchers interested in utilizing these data with information on the data integration process, how to access the data, and how to customize it to fit the needs of their research. The team will also engage with relevant stakeholders to identify or create strategies that may mitigate the unintended consequences of drug market disruptions (e.g., reduce overdoses and community violence), reduce disparities in these outcomes in communities of color, inform local and state law enforcement drug interdiction strategies, and inform the allocation of resources for drug interdiction.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非法物质的使用仍然是社会中持续且广泛的一部分，估计非法药物市场占全球总贸易的百分之一。尽管该市场的真实规模由于其非法，潜在的性质而未知，但总体的美国药物政策和战略一直是为执法机构分配大量资源以拆除非法分配网络。麻醉品执行的动机是，它暗示着供应方面的负面后果，这些后果都决定了人们无法分发非法药物并减少药物对脆弱消费者的可用性。然而，几乎没有证据表明负面后果破坏了宏观级别的药物供应，以改变药物的价格，而对这些固定剂对更广泛的社区和毒品消费者的暴力影响的中等水平影响，对致命过量过量的危险中的暴力影响很少。因此，这种破坏非法供应网络（D-ISN）项目的目的是利用国家综合数据来发展对执法破坏非法药物供应对公共卫生（例如过量服药）和公共安全（例如暴力犯罪）的影响的理解。为了了解药物市场中断与感兴趣的结果之间的关系，研究团队将使用三个行政数据来源在10个潜水员州构建一个计数水平数据集：（1）基于国家事件的报告系统（NIBRS），（2）国家健康统计中心（NCHS）详细的死亡原因（MCOD）数据（MCOD）数据，以及（3）US CESUS。 Nibrs捕获了犯罪事件的特征，包括以全国系统性的方式进行有关毒品癫痫发作，犯罪犯罪和其他事件特征的详细信息。 MCOD数据将根据死亡证明提供不受限制的，县级的死亡率信息，并包括有关原因，死者人口统计，死亡月份和县城市的信息。人口普查的数据将用于计算药物癫痫发作的速率和县级人口特征和资源剥夺的控制率。县级综合数据集将包括过量的日期（按毒品类型），公共安全事件（例如谋杀/非杀人罪，抢劫，抢劫和总攻击）以及发生结果的县。研究团队将采用空间临时灾难性建模的方法，该方法可以建模时间和空间特征之间的灾难性关系。最后，集成数据集将与有兴趣使用这些数据的研究人员共享有关数据集成过程的信息，如何访问数据以及如何自定义以满足其研究需求。团队还将与相关的利益相关者互动，以识别或制定可能减轻药物市场中断的后果（例如减少过量服用和社区违规）的意外后果，减少这些成果中这些结果的差异，在地方和州的执法毒品犯罪策略中为地方和州执法策略提供了依据，并宣布了dratuction dection nsf Icternotion nsf。利用基金会的知识分子和更广泛的影响审查标准。