Developing a Text-Based Measure of Humility in Inquiry Using Computational Grounded Theory

Abstract

We describe a project in which we develop a text-based measure of HI in the context of scholarly communication using corpora of scientific publications. The data and analytic approach we use will circumvent known concerns with self-reported data on humility levels and will be calculable on a large scale. We use a computational grounded theory approach to develop a text-based measure of HI. We draw from an annotated corpus of scientific articles in economics, psychology, and sociology (2010–2023), generating three supra-dimensions of HI (Epistemic, Rhetorical, and Transparent) and several novel sub-codes of HI. We present our initial analysis with a focus on the three dimensions of HI derived from a computational grounded theory approach. The text-based measure helps us better understand how contextual factors shape HI and contribute to mixed methods in information science research.