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Philanthropic Archives and Legacy

Bibliographic Data

ID12982183
AuthorsKatherine Badertscher (0000-0002-7127-969X, corresponding author), Huitan Xu
Year2025
Volume18
Issue1
Publication date2025-12-08
Open AccessYes
TypeARTICLE
VenueThe Foundation Review (JOURNAL)
Journal identifiersISSN: 1944-5660 • E-ISSN: 1944-5679
PublisherGrand Valley State University Libraries - DIGITAL COMMONS JOURNALS (PUBLISHER)
DOI10.9707/1944-5660.1745
OpenAlexW4417134993
LanguageEN

Grants fuel millions of organizations and advance social innovation across sectors. In the United States, foundations and corporations respectively awarded $103.5B and $36.5B to nonprofits in 2023 alone (Childress, 2024; Lilly Family School of Philanthropy, 2024). By extension, grant applications play a critical role in how grant recipients are identified and selected. While many funders are eager for more streamlined and equitable processes to review grant applications, the process remains primarily a manual and time consuming one (Hewlett Foundation, 2021). These factors leave some funders implementing grant application processes potentially at odds with their impact goals. Examples include restricting who can apply, including only application reviewers with specific credentials, or not screening for inconsistencies among reviewer assessments (Candid., n.d.). In this article, readers will learn how Missouri Foundation for Health and AI PRIORI® used artificial intelligence to inform a more effective, efficient, and equity focused application review process. Readers will gain insights into the experiments, AI tools used, and preparation and evaluation of data sets

Equity (law · Foundation (evidence · Grant funding · Health equity · Odds · Process (computing · Artificial Intelligence in Healthcare and Education · Delphi Technique in Research · Meta-analysis and systematic reviews

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