If you are a scientist, you have likely been confronted with the challenge of boiling down the work you do for various audiences. The simple act of saying how your day in lab went will be very different if you are talking with your roommate in the same graduate program, versus a family member who last took a science class in 1976. Earlier this month, I attended a talk given by Dr. Bruce Lewenstein, Professor of Science Communication at Cornell University, in which he shared some of the data on how to communicate science effectively. While the knowledge we have in this young field, which fuses science and the social sciences, is still evolving, the data-based guidelines he presented felt worthy of sharing with our PLOS ECR readership.
What is the science of science communication?
The science of science communication is more than just a pithy title. It is a field which has emerged over the past decade, which uses data to determine what works best for communicating science with different audiences. It asks how scientific knowledge can influence individuals’ decisions about personal and political issues, and what the data suggests scientists and researchers do to accurately convey their science in this landscape.
What has this field learned so far?
Dr. Lewenstein prefaced his entire talk by sharing that scientists must reframe how they think of “the public” in communicating their work.
“The first thing we know, is that there is no such thing as the public. There are many publics out there,” said Lewenstein. “They vary, and they change, and they go up and down. One of the biggest challenges is for us to constantly remember that there are many publics.”
With this in mind, Lewenstein delved into how older models for science communication have informed what the modern science of science communication field studies. He discussed three models, which are important to this growing field:
The deficit model, an older model, suggests that if there are scientific facts that the public does not know (a deficit of knowledge), providing the missing information will effect change in decision-making. Lewenstein shared data from the National Science Board’s Science & Engineering Indicators report, which has been tracking scientific knowledge for roughly 40 years. You can check out their extensive reports for yourself here. The report asks individuals various scientific knowledge questions, and tracks accuracy of answers over time.
The public engagement model, sometimes referred to as the dialogue model, suggests that publics know things that scientists don’t know, and that it is essential to consult these publics to answer scientific questions and make science policy decisions. Public engagement often goes hand-in-hand with the citizen science model, in which publics not only engage in discussions about science with scientists, but actively do the data collection or propose experiments. An example that Lewenstein gave was that of the water contamination crisis in Flint, Michigan. In Flint, it was citizens who reached out to scientists to together collect the data which ultimately forced politicians to take the problem seriously. These models of communication aim to formalize ways for communities to participate in science policy, and to empower communities to generate science themselves.
Today’s science communication scientists, like Lewenstein, seek to find what aspects of these models are most productive. Lewenstein recommended the American Academy of Arts & Sciences’ Perceptions of Science in America report for detailed recent data on these issues. But he summed it all up as two general conclusions:
- The science community needs to recognize that science necessarily engages with social issues. It is embedded in social institutions, like having graduate schools attached to hospitals, or receiving funding from taxpayer dollars.
- Ultimately, what matters is trust. It’s not about information, or the deficit model alone would work. It’s about trust, and that’s what is going to make changes in how people respond.
So how do I build trust amongst multiple types of publics?
This is the elephant in the room in these discussions—building trust is hard. And generally, most publics already have established communities that they trust. Lewenstein showed data that indicated people who correctly answer scientific questions, may still believe something else which is more aligned with beliefs in their community (ex. individuals who are more religious know what the theory of evolution is, but still believe creationism). Understanding the nuances of knowledge and belief is important to consider in these discussions. It seemed to me that a key way to build trust between scientists and publics, is to put time and effort into relationships we have outside of the lab. Try to maintain friendships within multiple communities, so that you can contribute to the communal knowledge of the group.
Lewenstein left us with a concise TL;DR slide for communication tactics, which I’ll share here as well:
- Don’t assume facts are the issue.
- When correcting misinformation, don’t repeat it.
- Provide a clear thematic story (not an individual victim).
- Provide an identifiable scientist.
- Don’t fall into an “us vs. them” trap.
Lewenstein’s Cornell profile has tons of resources for learning more about these topics, and the reports mentioned here are also full of interesting data. Lewenstein also kindly sent along the following resources when I wrote to him about this post:
- Recent Pew reports have data on public perception of science:http://www.pewresearch.org/science/.
- The AAAS Public Engagement pages are also informative — https://www.aaas.org/programs/center-public-engagement-science-and-technology and https://www.aaas.org/resources/communication-toolkit.
- In mid-February, the American Academy plans to release a follow-up to the ‘Perceptions’ report on ‘Encountering’ science, with specific suggestions for public engagement. Keep an eye out!
And maybe listening to our communities can teach us even more.
Lewenstein, Bruce, Communicating Science in a Polarized Environment, Weill Cornell Graduate School Science and Society Series, January 9, 2019.
Lewenstein, Bruce, Cornell University http://blogs.cornell.edu/lewenstein/.
National Science Board, Science & Engineering Indicators 2018 https://www.nsf.gov/statistics/2018/nsb20181/
American Academy of Arts and Sciences, Perceptions of Science in America https://www.amacad.org/publication/perceptions-science-america
Suldovsky, Brianne, The Information Deficit Model and Climate Change Communication, Oxford Research Encyclopedia, http://oxfordre.com/climatescience/view/10.1093/acrefore/9780190228620.001.0001/acrefore-9780190228620-e-301.
Hetland, Per, Models in Science Communication: Formatting Public Engagement and Expertise, Duo Research Archive, 2014 https://www.duo.uio.no/handle/10852/42035.
Featured image: Ron Mader https://www.flickr.com/photos/planeta/35539215105 No changes were made to this image. https://creativecommons.org/licenses/by-sa/2.0/