By David W. Cash, Dean, John W. McCormack Graduate School of Policy and Global Studies University of Massachusetts Boston; +1-617-794-9431; email@example.com
The Biden-Harris Administration will need to re-construct the scientific infrastructure of federal agencies whose staff, processes and institutions are severely diminished. In order to address the four priorities of COVID-19, racial equity, climate change, and economic recovery, building science back better will be critical.
Traditional approaches applying science in policy making arenas focus on the credibility of the science – how well the science meets standards of technical adequacy driven by peer review and processes that evaluate methodology and evidence. Credibility is necessary, but not always sufficient in building trust in science, especially when working in areas that are characterized by political conflict. Two other characteristics of science may be equally important: salience and legitimacy. Salience is the relevance of the science to decision makers or stakeholders – is science asking the questions that matter to them? Legitimacy relates to whether the process of creating knowledge has been transparent, fair, inclusive of divergent views or values, and as unbiased as possible.
Building science back better will certainly mean re-establishing the credibility of government science. But a further focus by federal agencies on creating the right institutions and processes to advance the salience and legitimacy of science will increase the chance that government science will make a difference in solving the major challenges we face. Enhancing the relevance of science and assuring that it is legitimate will require intentional efforts that deliberately bridge the boundary between science and decision making and/or communities. Such mechanisms maintain participatory processes that support communication and translation across the boundary; engage stakeholders early and often in the scoping of analysis; disaggregate data by race, income, gender and other variables in ways that have particular resonance at local levels; and jointly create and own data, tools, maps or models that explore problems and test solutions.
A compelling example is the agricultural extension system in the United States, which, for over a century, has effectively linked agricultural research at land grant colleges to the everyday decisions of farmers. The system of county extension agents connects the concerns, questions, and innovations of farmers to scientists at land grant colleges, and supports iterated two-way communication that enhances credibility, salience, and legitimacy of the science. The result is a relatively high degree of trust between farmers and scientists and the deployment of science and technology that assists farmers at local levels. Through the bridging actions of the county extension office, farmers help scope research, are part of building and using agro-economic models, and become innovators of new technology and practices.
What are the prospects of using this kind of framework in addressing the four policy priorities of the early Biden-Harris Administration? The examples below simplify complex systems, but they highlight the kinds of efforts and organizations that can help build trust in science to solve these challenges.
- COVID-19: As the COVID crisis hit in early 2020, the disaggregation of data that showed which communities by race were hit the hardest enabled such communities to mobilize, for example, with targeted distribution of PPE. Similarly, as vaccines become available, successful deployment will depend on local adoption, and designing processes so that communities trust that the vaccines will be safe and effective. Linking national systems of vaccine distribution to local trusted organizations (e.g., local community health care centers, houses of worship, etc.) may facilitate the ability for local community members to air concerns (ask the questions that are salient to them), and be part of the process of creating a distribution system that is transparent, accountable, and has local ownership.
- Racial equity: Social sciences play a large part in understanding inequitable structures and biases in wealth, government, health care, housing, policing, and education. For example, by disaggregating wealth data by income, race, gender, and geography, analysts, decision makers, and communities can see disparities in economic variables. In addition, numerous academic institutions and even the Federal Reserve have launched a variety of different kinds of community-engaged action research programs, linking researchers to communities so that participatory engagement in the scoping and conducting of research establishes long-term trusted relationships with communities to both examine the root causes of inequities and propose, pilot, and implement solutions.
- Climate change: There is now a long record of global through local systems that link science and decision making through robust organizations and processes that engage decision makers and scientists in iterated participatory networks that enhance trust in science through downscaling climate data and models, running state and local-scale risk assessments, and exploring locally driven policy scenarios. NOAA’s Regional Integrated Sciences and Assessments (RISA) program is one such example. Emerging renewable energy extension programs that piggy-back on the agricultural extension system is another.
- Economic recovery: One part of economic recovery will be job training and workforce development. These are inherently local concerns driven by local industry, markets, and economic indicators, but are influenced by larger scale forces. As is already in place, federal-state-local integrated workforce development programs can be resourced to assure that solutions fit local conditions and are informed both by federal statistics and economic data from trusted local sources. The result of the use of such trusted data can drive growth in sectors that will generate long-term prosperity.
As government science is reconstituted in the Biden-Harris Administration, there is a window of opportunity to re-build better by focusing on all three of these attributes of science – credibility, salience and legitimacy. Such focus will increase the chance that science will drive better decision making, especially in a complex and politically charged world.
For more reading:
Matson, P., W.C. Clark, and K. Andersson (2016) Pursuing Sustainability: A Guide to the Science and Practice, Princeton University Press.
Cash, D.W., W.C. Clark, F. Alcock, N.M. Dickson, N. Eckley, D. Guston, J. Jäger and R. Mitchell (2003). Knowledge Systems for Sustainable Development. Proceedings of the National Academy of Sciences of the United States of America 100: 8086-8091.