Dietram A. Scheufele

Escaping) the paradox of scientific storytelling

Compelling stories about science can motivate people to engage and respond to relevant problems facing society. While science plays a unique role in society, providing the best available evidence for policy choices, understanding the world, and informing citizens’ daily lives, it does not hold any intrinsic advantage in creating captivating stories for mass audiences. Instead, science must compete with other storytellers, many of whom are not bound to scientific evidence. This presents a paradox—how can science preserve its credibility as curator of knowledge while engaging audiences with a communication format that is agnostic to truth?

Beyond the Choir? The Need to Understand Multiple Publics for Science

ABSTRACT Understanding different publics for science communication is more important than ever before. The articles in this special issue lay important groundwork for our field to develop a better understanding of how audience segments differ or overlap across issues, cultural contexts, stages of the issue cycle, and different analytic and methodological approaches. The long-term goal of this work should be to enable more effective communication with publics whose demographic, socio-structural, or value-based characteristics position them squarely outside of the proverbial choir that science communication is often preaching to.

National Academies of Sciences, Engineering, and Medicine report on genetically engineered crops influences public discourse

Abstract. In May 2016, the National Academies of Sciences, Engineering, and Medicine (NASEM) released the report “Genetically Engineered Crops: Experiences and Prospects,” summarizing scientific consensus on genetically engineered crops and their implications. NASEM reports aim to give the public and policymakers information on socially relevant science issues. Their impact, however, is not well understood. This analysis combines national pre- and post-report survey data with a large-scale content analysis of Twitter discussion to examine the reports effect on public perceptions of genetically modified organisms (GMOs). We find that the reports release corresponded with reduced negativity in Twitter discourse and increased ambivalence in public risk and benefit perceptions of GMOs, mirroring the NASEM reports conclusions. Surprisingly, this change was most likely for individuals least trusting of scientific studies or university scientists. Our findings indicate that NASEM consensus reports can help shape public discourse, even in, or perhaps because of, the complex information landscape of traditional and social media.

Communicating data: interactive infographics, scientific data and credibility

Information visualization could be used to leverage the credibility of displayed scientific data. However, little was known about how display characteristics interact with individuals’ predispositions to affect perception of data credibility. Using an experiment with 517 participants, we tested perceptions of data credibility by manipulating data visualizations related to the issue of nuclear fuel cycle based on three characteristics: graph format, graph interactivity, and source attribution. Results showed that viewers tend to rely on preexisting levels of trust and peripheral cues, such as source attribution, to judge the credibility of shown data, whereas their comprehension level did not relate to perception of data credibility. We discussed the implications for science communicators and design professionals. Abstract

Developing the User Experience for a Next Generation Nuclear Fuel Cycle Simulator (NGFCS)

With its recent roadmap for research, development and deployment (RD&D), the US Department of Energy’s Office of Nuclear Energy (DOE-NE) seeks to ensure that nuclear energy continues to be a competitive energy option for decades to come. Development of sustainable fuel cycles has been identified as a primary challenge. Continued research in technologies that support such fuel cycles will be conducted in the coming decades in order to support an ultimate decision for the path forward. RD&D decisions for individual nuclear energy technologies must be informed by the technical, political and socio-economic impacts of those technologies on the whole nuclear energy system. Therefore, the Fuel Cycle Research & Development program is developing a next generation fuel cycle simulator (NGFCS) with sufficient modularity to accommodate a wide variety of audiences, use cases and developer needs. The NGFCS is expected to be a useful evaluation tool for a variety of audiences. Non-technical audiences will interact with the NGFCS in a way that allows them to express critical high-level decisions and understand the outcomes of those decisions in a set of key metrics. Expert audiences may be interested in a quantitative technology assessment to help motivate design improvements. Developers of the NGFCS will need to visualize their results to ensure consistency and correctness. At the same time, it is important that the NGFCS allow experts to introduce new modules to capture specific physical models or market behavior, but rely on a common infrastructure that facilitates direct comparisons of results. This university team will focus on the design and development of the user experience for a next generation nuclear fuel cycle simulator (NGFCS), based on the software requirements and design developed in conjunction with the Fuel Cycles Technologies Systems Analysis Campaign. In addition to ensuring an adequate user environment for developers, including input generation and detailed quantitative output visualization, particular attention will be paid to the policyand decision-maker audience that may be interested in trends and trade-offs in a more qualitative manner. An interdisciplinary team will combine research in social science, computer science and nuclear engineering to support an innovative interface for nuclear fuel cycle systems analysis. This project will have five thrusts, conducted in parallel and integrated into a unified effort:  Identification of priority stakeholders, input parameters and output metrics  User interface for model generation using input parameters  Data translation to derive output metrics  Visualization environment for analytic reasoning and data exploration  Efficient Design of Client-Server Model