NCRN-MN: Data Integration, Online Data Collection, and Privacy Protection for Census 2020

NCRN-MN：2020 年人口普查的数据集成、在线数据收集和隐私保护

• 批准号: 1130706
• 负责人: William Eddy
• 金额: $ 299.95万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1130706&HistoricalAwards=false
• 关键词: NCRN; MN; Data; Integration; Online

This project will conduct research on three basic issues of interest related to the conduct of censuses: privacy, costs, and response rates. The researchers will address the practical problems of insuring confidentiality and privacy while still producing useful data for public and private purposes. In terms of cost issues, the researchers will investigate the use of administrative records to create a basic census frame, saving the duplicated effort of gathering that same information repeatedly, as well as other possible uses of administrative records as part of the census. They also will investigate the use of online data collection as a substitute for the traditional mail-out/mail-back census-taking. With respect to response rates, the researchers will conduct experiments that implement new ways of encouraging participation in an effort to reduce the decline in (or perhaps even increase) response rates.This research will explore the potential for a significant reduction in the costs of conducting the 2020 census by demonstrating how information already collected by the government can serve as a starting point for the census in lieu of having the Census Bureau collect that information anew as part of the decennial census process. By learning to effectively use the Internet for censal data collection, the research should lead to a higher initial response rate, and hence lower census costs overall, and a more accurate count. Better methods for confidentiality protection and privacy notification not only will instill greater public confidence in the Census Bureau, but they also will contribute to better response rates and greater census accuracy. All of the technical statistical tools developed by the project will have other uses, both public and commercial. The project's educational and training initiatives aim to (1) prepare an educated citizenry on census and related matters, (2) use research issues under study at CMU and elsewhere as components in courses, and (3) train a new generation of students to enable them to work in agencies such as the Census Bureau in a diverse set of capacities, including the most technically demanding ones. This activity is supported by the NSF-Census Research Network funding opportunity.

该项目将研究与人口普查有关的三个基本问题：隐私、费用和答复率。 研究人员将解决确保机密性和隐私性的实际问题，同时仍然为公共和私人目的提供有用的数据。 在成本问题方面，研究人员将调查使用行政记录来创建基本的人口普查框架，节省重复收集相同信息的重复工作，以及作为人口普查一部分的行政记录的其他可能用途。 他们还将调查使用在线数据收集来替代传统的邮寄/邮寄普查。 关于答复率，研究人员将进行实验，实施鼓励参与的新方法，以减少参与率的下降。（甚至可能增加）这项研究将通过展示政府已经收集的信息如何作为人口普查的起点，而不是作为人口普查的起点，探索大幅降低2020年人口普查成本的潜力。让人口普查局重新收集这些信息，作为十年一次的人口普查过程的一部分。 通过学习有效利用互联网收集普查数据，研究应能提高初步答复率，从而降低普查的总体成本，并使统计更加准确。 更好的保密保护和隐私通知方法不仅会增强公众对人口普查局的信心，而且还有助于提高答复率和人口普查的准确性。 该项目开发的所有技术统计工具都将有其他用途，包括公共用途和商业用途。 该项目的教育和培训举措旨在：（1）培养受过普查和相关事项教育的公民;（2）将CMU和其他地方正在研究的研究问题作为课程的组成部分;（3）培训新一代学生，使他们能够在人口普查局等机构以各种能力工作，包括技术要求最高的能力。 这项活动得到了NSF-人口普查研究网络资助机会的支持。