NSF – Human-Environment and Geographical Sciences (HEGS)
Posted November 6, 2024
Disciplines: All
Interested in this opportunity? Consider taking advantage of the Hanover Queue for Proposal Review. Contact Dr. Liz Cali for more information. [email protected]
Click here for more information about the Hanover Research Grant Proposal Support.
The objective of the Human-Environment and Geographical Sciences Program is to support basic scientific research about the nature, causes, consequences, or evolution of the spatial dimensions of human behaviors, activities, and dynamics as well as their interactions with environmental and social processes across a range of scales. Contemporary geographical research encompasses diverse research traditions and methodologies. Recognizing the breadth of the field’s contributions to science, the HEGS Program welcomes proposals for empirically grounded, theoretically engaged, methodologically rigorous, and generalizable research that advances geographical and geospatial sciences.
Because the National Science Foundation's mandate is to support fundamental scientific research, the HEGS program cannot fund research that takes as its primary goal humanistic interpretations or findings that are not generalizable or reproducible. HEGS welcomes proposals that utilize quantitative, qualitative, or mixed methods in novel ways. However, a proposal that applies geographical or geospatial methods to a geographic problem without proposing how that problem provides an opportunity to make a theory-testing or theory-expanding contribution to geographical science, broadly defined, will be returned without review. HEGS supported projects are expected to yield results that will enhance, expand, and transform fundamental geographical theory and geospatial methods and that will have broader impacts that benefit society.
Generally, successful HEGS proposals should describe clear and detailed plans for data collection (including sample selection if appropriate), justification for proposed methods, plans for data analysis, attention to confounding variables, and efforts to address biases (e.g., confirmatory biases, selection biases, etc.). Competitive HEGS proposals should substantiate the validity of findings and generalizability to broader contexts.
Full Proposal due February 3, 2025
