HDR Candidate: Christopher Shadforth

Title: The Development of Contextual Understanding for Information Use in Geoscience

Time and date: 9-11am, Tuesday 1 February 2022

Zoom linkhttps://uqz.zoom.us/j/9416028503



The meaning of information is not purely objective – we need to interpret signals within a context. Much of daily life can occur without conscious consideration of the contextual understanding we interpret information within. However, novel problems or deviations from the standard can require substantial consideration of context to integrate information into a coherent understanding of a problem. This dissertation contributes to filling this gap in economics on this problem of forming contextual understanding through a study of the processes of geoscientists in forming a contextual understanding. Geoscience projects are filled with uncertainty, indirect measurements, interactions between causal systems, the use of both quantitative and qualitative information, and the need to negotiate interpretations of the data. This means the development of contextual understanding is an integral part of the use of information by geoscientists.

Chapter 1 details an exploratory interview study with geoscientists of different experience levels from academia, industry, and government. During the interviews, the focus of the study shifted from direct interpretation of information to the formation of the contextual understanding within which interpretation occurs. The results show that geoscientists consider several contexts in forming a contextual understanding, in particular the personal context, data context and project context. The elements and processes of these contexts are considered, and connections made between the findings and prior literature. Based on these results, Chapter 2 is an experiment with student participants on the effect of familiarity bias and complexity preferences on the choice of information methods. Chapter 3 concludes with a framed field experiment using geoscientists and a contextually appropriate stylised example, building upon the design of the first experiment and testing policy solutions.