Historical systematic exclusionary tactics based on race have forced people of certain demographic groups to congregate in specific urban areas. Aside from the ethical aspects of such segregation, these policies have implications for the allocation of urban resources including public transportation, healthcare, and education within the cities. The initial step towards addressing these issues involves conducting an audit to assess the status of equitable resource allocation. However, due to privacy and confidentiality concerns, individual-level data containing demographic information cannot be made publicly available. By leveraging publicly available aggregated demographic statistics data, we introduce PopSim, a system for generating semi-synthetic individual-level population data with demographic information. We use PopSim to generate multiple benchmark datasets for the city of Chicago and conduct extensive statistical evaluations to validate those. We further use our datasets for several case studies that showcase the application of our system for auditing equitable allocation of city resources.

翻译：历史上的系统性种族排斥策略迫使特定人口群体聚集在城市特定区域。这种隔离不仅涉及伦理问题，更对城市内部公共交通、医疗保健和教育等资源的分配产生深远影响。解决这些问题的首要步骤是对资源公平分配状况进行审计。然而，受隐私保密限制，包含人口统计信息的个人级数据无法公开获取。我们通过利用公开的聚合人口统计数据，提出PopSim系统——一种可生成含人口学特征半合成个人级人口数据的系统。我们运用PopSim生成芝加哥市的多个基准数据集，并通过广泛统计评估验证其有效性。进一步地，我们利用这些数据集开展多项案例研究，展示该系统在城市资源公平分配审计中的应用。