Paper No. 191-2
Presentation Time: 9:00 AM-6:30 PM
QUANTIFYING GEOSCIENCE COMMUNICATION AND ITS IMPACT
Statistical techniques provide novel insights into geoscience communications and their utility. This talk focuses on three key themes: (1) science communications to the public through a protracted natural disaster sequence, (2) multi-disciplinary science communications and their impact on decision-making under conditions involving risk and uncertainty, and (3) linguistic advocations for science by U.S. Presidents. Analysis of science website traffic during the 2010–2012 Canterbury earthquake sequence in New Zealand reveals near-instantaneous surges in science website after strong earthquakes followed by power-law temporal decay consistent with Omori's (1895) law for aftershocks. Website traffic is ultimately sustained at volumes must larger than pre-disaster rates, providing clear evidence for enhanced public use of geoscience communication websites that respond rapidly and efficiently to natural disasters. Science provisions to decision-makers are investigated for seven earth science case studies and classified on the basis of (i) scientific consensus amongst inputs and (ii) volume of relevant and available science used in decision-making. Evidence for collaborative, nonlinear engagement between decision-makers and science providers, including use of diverse science communication pathways is presented. Under-utilized science provider actions that could be further explored as avenues to enhance geoscience communication strategies are defined. Advocations for science by the Presidents of the United States, from Truman to Trump, are quantitatively analysed using keyword frequency, principal component, and hierarchical clustering analyses. The strongest advocates for science have the highest mean presidential approval ratings and greatness survey scores. Leaders that advocate for science within complex socio-political environments may be more politically successful than those who do not, although a causal link among these parameters is not necessarily implied.