HNDS-I: Collaborative Research: Developing a Data Platform for Analysis of Nonprofit Organizations

HNDS-I：协作研究：开发用于分析非营利组织的数据平台

• 批准号: 2024320
• 负责人: Calton Pu
• 金额: $ 81.36万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024320&HistoricalAwards=false
• 关键词: HNDS; Collaborative; Research; Developing; Data

Nonprofit organizations are important contributors to the US economy and social well-being. Across a wide range of domains, such as healthcare, childcare, education, job training, and many others, nonprofit organizations serve the public, reduce the costs of government, and improve daily lives. Millions of individuals interact with nonprofit organizations every day. Yet despite these important roles, the high costs of collecting and sharing data have prevented a greater understanding of nonprofit organizations and their collective contributions to society. This project, the Nonprofit Organization Research Panel Project (NORPP) Manager, will create a publicly-accessible, internet-based, and collaborative research platform that will lower the costs of collecting and sharing large amounts of high-quality, multiyear data on nonprofits and their impacts. The platform will strengthen research and evaluation, broaden access to data-intensive research, and lead to more scientifically informed decision-making by organizations, policymakers, and funders and to improved outcomes for the communities they serve.The NORPP platform will offer three primary functions. First, tools and automated processes will allow researchers to recruit and grow representative samples of nonprofit organizations nationally and across communities, states, and regions over time using a common methodology. The platform will automate systematic sampling and weighting procedures to ensure representativeness for studies using the platform, and it will reduce other costs to researchers by automating information flows with organizations in its samples. It will also allow public access among the research and practice communities to download nationally representative data, build additional project-specific samples within the platform, add original survey instruments, and collect original data. Second, the NORPP Manager will support the merger of data developed within the platform with IRS Form 990 Data and other available data on organizations from the population of 501(c)(3) nonprofit organizations that file with the IRS, including geocoded data on organizations’ communities and external environment that are publicly available from Census and other sources. Third, the NORPP Manager will serve as a collaborative repository to manage a bank of core and supplemental questionnaires to facilitate replication studies, improve content validity of measurements, and allow for consistent measurement scales across nonprofit organizational research. This work will increase the efficiency of research on nonprofit organizations by significantly reducing the costs to sample, contact, and survey nonprofit organizations, and to merge those data with existing data with the goal of facilitating the growth of rigorous, data-intensive research across the many social science disciplines that intersect with nonprofit organizational research.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.

非营利组织是美国经济和社会福祉的重要贡献者，在医疗保健、儿童保育、教育、职业培训等众多领域，非营利组织为公众服务，降低政府成本，每天都有数百万人与非营利组织互动，但收集和共享数据的高昂成本阻碍了人们更好地了解非营利组织及其对社会的集体贡献。面板项目 (NORPP) 经理将创建一个公开访问、基于互联网的协作研究平台，将降低收集和共享有关非营利组织及其影响的大量高质量、多年数据的成本。该平台将加强研究和评估，扩大对数据密集型数据的获取。 NORPP 平台将提供三个主要功能，首先，工具和自动化流程将允许研究人员招募和成长。全国和各地非营利组织的代表性样本随着时间的推移，该平台将使用通用方法自动执行系统抽样和加权程序，以确保使用该平台的研究的代表性，并且通过自动化样本中的组织的信息流来减少研究人员的其他成本。还允许研究和实践社区之间的公众访问下载具有全国代表性的数据，在平台内构建额外的特定项目样本，添加原始调查工具并收集原始数据。其次，NORPP 管理器将支持合并内部开发的数据。带有 IRS 表格 990 的平台向 IRS 备案的 501(c)(3) 非营利组织群体的数据和其他可用数据，包括可从人口普查和其他来源公开获得的组织社区和外部环境的地理编码数据。 Manager 将作为一个协作存储库来管理一系列核心和补充问卷，以促进重复研究，提高测量的内容有效性，并在非营利组织研究中实现一致的测量尺度。这项工作将通过以下方式提高非营利组织的研究效率。显着减少抽样、联系和调查非营利组织的成本，并将这些数据与现有数据合并，目的是促进与非营利组织研究交叉的许多社会科学学科中严格的数据密集型研究的发展。该奖项是 NSF 的法定奖项使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。