HNDS-R: Population-Scale Kinship Networks and Migration

从遗传病的流行到老年人的照顾，亲属关系在社会中发挥着重要作用。亲属关系已被证明在为移民提供支持方面特别重要，而移民反过来又向家乡的亲属汇款，但用于研究当代移民的典型方法无法显示其对空间亲属网络的长期影响。需要更大时间和空间尺度的数据。该项目创建了一个人口规模的家谱数据集，将大约4000万人的众包家谱与他们的共同祖先联系起来。这项研究将利用这些数据来研究几个世纪以来，移民是如何影响亲属的地理邻近性的。该项目通过在人际网络和数据科学领域培训研究生、本科生和高中生，有助于培养具有全球竞争力的STEM劳动力。它开发了一种在线视觉叙事和教育工具，以传播移民如何形成文化和人口结构。这一工具是通过与高中社会研究教师合作开发的，有可能提高公众对移民和亲属网络研究的科学素养和参与度。本研究比较了亲属网络在不同条件下的空间演变，以检验不同类型的网络如何以及何时出现、停滞和最终消失的理论，并展示了这些网络如何随着各种经济和人口环境而变化。该项目将历史人口普查数据中的职业、家庭组成和住宅的精细位置等信息与家谱联系起来。这些数据可以用来描述亲属网络及其在地理空间和时间上的演变。这项研究有助于揭示有利于相关家庭大规模聚集发展的条件，以及那些有利于分散的条件。具体而言，该项目评估了移民对不同类型网络发展的贡献程度，以及随着不同群体在不同地点定居，这种关系如何变化。本研究通过开发新的测量方法、模型和可视化技术来研究亲属网络与迁移之间的关系，有助于弥合地理信息科学与社会网络分析之间的差距。这些数据将使研究人员能够研究家庭成员的接近程度如何影响其他各种长期的多代结果，如收入不平等、社会流动性和健康。更好地了解改变亲属网络的力量和描述这些力量的方法，有助于预测当前和未来的变化，例如老年人或弱势群体可以在多大程度上依赖附近亲属的支持。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。

From the prevalence of genetic diseases to provision of care for elderly, kinship plays an important role in society. Kinship has been shown to be particularly important in providing support to migrants, and migrants, in turn, send money to relatives back home, but the typical methods used to study contemporary migration cannot show its long-term effects upon kin networks in space. Data at a larger temporal and spatial scale are needed. This project creates a population-scale family tree dataset which links about forty million people in crowd-sourced family trees to their common ancestors. The research will use these data to study how migration influenced the geographic proximity of kin over centuries. This project contributes to the development of globally competitive STEM workforce by training graduate, undergraduate and high school students in the areas of human networks and data science. It develops an online visual storytelling and education tool to communicate how migrations form cultural and demographic structures. This tool, which is being developed through a collaboration with high school social studies teachers, has the potential to increase public scientific literacy about and engagement in the study of migration and kinship networks.This research compares the spatial evolution of kinship networks under different conditions to test theories about how and when different types of networks emerge, stagnate, and, ultimately, disappear, showing how those networks change as a result of a variety of economic and demographic circumstances. The project links information such as occupation, household composition, and fine-scale locations of residences from the historical census data to the family trees. This data can then be used to characterize kinship networks and their evolution over geographic space and time. This research helps reveal the conditions that favor the development of large aggregations of related families, and those that favor dispersion. Specifically, this project assesses how much migration contributed to the development of different types of networks and how this relationship changed as different locations were settled by different groups. This research helps bridge the gap between geographic information science and social network analysis by developing new measures, models, and visualization techniques for studying the relationship between kinship networks and migration. The data will allow researchers to study how the proximity of family members influences a variety of other long-term multi-generational outcomes such as income inequality, social mobility, and health. A better understanding of the forces that transform kinship networks and methods for describing them helps anticipate changes in the present and future, such as the extent to which elderly or vulnerable populations can rely on kin nearby for support.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.