Collaborative Research: US Forest Service Decisions and Innovations

Project: Research project

Project Details

Description

Effective public decision-making requires an evidence-based approach, and leading scientists frequently call for producing policy-relevant science, yet little is known about how government officials use science in their day-to-day work. This project will fill this gap by conducting a systematic analysis of use of science in thousands of decisions about environmental policy made at multiple levels of the US federal government. We focus on the contents of Environmental Impact Statements (EISs) prepared by the US Forest Service (USFS) under the National Environmental Policy Act. Providing a more detailed picture of how scientific information is used in government decision-making will enable government agencies to improve the processes through which they incorporate scientific information. At the same time, providing details of what types of scientific information are utilized in public decision-making processes will help scientists, universities, and funding agencies prioritize science that is policy-relevant. To forward these goals, the project will publish an index that will assist scientists in comparing the policy impact of different publications and will conduct outreach activities with environmental planners to help them understand the implications of the research.

This project will use web scraping and computational text analysis to collect and analyze the use of science in all USFS EISs produced between 2006 and 2018. These EISs record the scientific basis for at least 2,000 decisions made about public land management in a wide variety of contexts. The project has two objectives: (1) Understand what drives the inclusion of innovative scientific information (data, facts, evidence) in USFS EISs; and (2) Understand what drives the adoption of innovative scientific practices (operating procedures, protocols, norms) by USFS decision-makers preparing EISs. Using computational text analysis and machine learning tools, we will measure various aspects of the scientific content of each document such as citations, key concepts, and analytical practices. We will combine this information with publicly available data about the scientific information in each document, such as place of publication, employer of the scientists producing the document, extent of public participation in the document's preparation, and the government office using the scientific information. This analysis will help in understanding how characteristics of scientific information and characteristics of government offices influence how science is used in public decision-making processes.

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.

StatusFinished
Effective start/end date9/1/188/31/23

Funding

  • National Science Foundation: $374,239.00

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