Collaborative Research: Routine Maintenance of Registration Lists

包含有关人员信息的数据库需要定期关注，以便在个人移动、死亡、变得不活跃或以其他方式更改状态时保持更新。因此，必须定期更新州和地方登记名单，以防止数据的完整性和有用性下降。然而，在美国各地，用于维持登记名单的具体做法因当地条件和传统而异。在大流行期间实施的数据更新选择的影响尤其难以理解。因此，本项目调查人口数据与登记名单更新之间的关系。在这种情况下，社会学关注的变量包括所使用的程序、负责这一过程的官员、社区的社会人口特征以及新冠肺炎的区域影响。为了检验关于这些变量的假设，该项目编制了一个开放的清单维护程序数据库，可作为公共资源。这可以帮助学者、数据科学家和决策者更好地了解可用的替代方案，以保护此类列表的可访问性、准确性和安全性。 在美国所有50个州，该项目将匹配有关登记名单、个人人口统计数据、社区和官员的社会经济特征、名单维护程序以及COVID-19中断和应对的数据。这项研究将使用纵向，多层次和空间分析，以测试假设不同的方式进行维护登记名单。该项目由社会学计划和激励竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了NSF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。

Databases that contain information about people need regular attention to keep them up-to-date as individuals move, die, become inactive, or otherwise change status. The refreshing of state and local registration lists must therefore take place periodically to prevent the integrity and usefulness of the data from degrading. Across the United States, though, the particular practices used to maintain registration lists vary with local conditions and traditions. The effects of data-updating choices implemented during the pandemic are particularly hard to understand. This project therefore investigates the relationship between demographic data and registration list updates. Variables of sociological interest in this context include the procedures used, the officials responsible for the process, the socio-demographic characteristics of communities, and the regional effects of Covid-19. To test hypotheses about these variables, the project compiles an open database of list maintenance procedures that can serve as a public resource. This can help scholars, data scientists, and decision-makers better understand the menu of alternatives available to protect the accessibility, accuracy, and security of such lists. Across all 50 U.S. states, the project will match data about registration lists, the demographics of individuals, the socioeconomic characteristics of their communities and officials, list maintenance procedures, as well as COVID-19 disruptions and responses. The study will use longitudinal, multilevel, and spatial analysis to test hypotheses about different ways of performing maintenance on registration lists. This project is jointly funded by the Sociology Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.