Appealing to the Authority of Data: Social Complexity, Fragmented Decisionmaking, and the Politics of Smart Cities

城市决策者如何使用信息？他们如何有效地利用信息？定义有用信息的问题的横切定义是什么？城市中通过多种决策路径进行的分散决策如何影响信息的使用方式？该项目将研究地方政府内部的组织，以分析城市如何定义问题和使用数据，分解政策决策。共同调查人员将研究行政能力不同的司法管辖区，将每个城市的关键线人认为重要的政策问题作为案例。城市正处于一个信息日益丰富的环境中，在数据分析方面不断增加的投资将迫使城市官员使用信息。我们对大城市之外的数据分析实践是如何运作的知之甚少。在智力上，该项目将有助于问题的理论化，决策的优先次序和信息的使用。该项目更广泛的影响将包括协助各城市制定一个程序，就对它们最有用的信息提出问题，并在各辖区传播调查结果。该项目将召开会议，帮助地方政府改善信息流通，提高措施的适当性。最后，该项目将以多种方式培养研究生。在现有的项目中，许多学生是非传统的学生，他们是种族化的少数民族的成员，为扩大社会科学的参与做出了贡献。个案的选择是根据行政能力和规模的不同。依靠机构民族志、关键线人访谈和文件分析，该项目将追踪对数据有用性的理解，特别是从数据到行动的转化。该框架是基于社区的研究，举报人也可从其他参与者和司法管辖区获得有关进程和理解的反馈。因此，由于该项目将不同的组织聚集在一起开发和使用数据，它也将召集参与者分享不同的理解，协作定义问题和可能的解决方案，并与社区成员讨论问题定义，数据分析和潜在的解决方案。这种方法将意味着，随着项目的进展，城市官员、城市公民和居民、设计师、用户和选民将从这个过程中受益。该项目将展示信息和决策流程的软系统模型。最后，合作pi将使用在前几个阶段收集的信息来开发基于代理的模型，以协助决策者。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

How do decision makers in cities use information? How can they use information effectively? What are cross cutting definitions of problems that define the information that is useful? How does the fragmented decision-making via multiple policymaking paths in cities shape how information is used? This project will study organizations within local governments to analyze variation in how cities define problems and use data, disaggregating policy decision-making. Co-PIs will study jurisdictions that vary in administrative capacity, using as a case a policy issue that key informants in each city define as significant. Cities are in an increasingly information rich environment, and increasing investments in data analytics will press city officials to use information. We know little about how the practice of data analytics works outside of large cities. Intellectually, the project will contribute to theorizing problem formulation, priorities in decision-making and use of information. The project's broader impacts will include assisting cities in developing a process for formulating questions about the information that will be most useful for them, and disseminating findings across jurisdictions. The project will convene meetings that help local governments to improve the flow of information and to improve the appropriateness of measures. Finally, the project will train graduate students in multiple methods. Many of the students in the available programs are non-traditional students who are members of racialized minorities, contributing to broadening participation in the social sciences.Cases have been selected for variation in administrative capacity and size. Relying on institutional ethnography, key informant interviews, and analysis of documents, the project will trace understandings of the usefulness of data and specifically the translation from data to action. The framework is community-based research, where informants also get feedback on processes and understandings from other participants and jurisdictions. Therefore, as the project brings different organizations together to develop and use data, it will also convene participants to share the different understandings and to collaboratively define problems and possible solutions, and to discuss problem definitions, data analytics, and potential solutions with community members. That approach will mean that city officials, and cities' citizens and denizens, as designers, users and constituents will benefit from the process as the project progresses. The project will surface a soft systems model of information and decision-making flows. Finally, the co-PIs will use the information gathered in previous phases to develop an agent-based model to assist decision makers.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.