Subjective Logic as a Complementary Tool to Meta-Analysis to Transparently Address Second-Order Uncertainty in Research Findings

Any experiment brings about results and conclusions that necessarily have a component of uncertainty. Many factors influence the degree of this uncertainty, yet they can be overlooked when drawing conclusions from a body of research. Here, we showcase how Subjective Logic could be employed as a complementary tool to meta-analysis to incorporate the chosen sources of uncertainty into the answer that researchers seek to provide to their research question. We illustrate this approach by focusing on a body of research already meta-analyzed by one of us, whose overall aim is to assess if human infants possess an intuitive moral sense. We show how each finding can be encoded as a subjective opinion, and how findings can be aggregated to produce an answer that explicitly incorporates uncertainty. We argue that a core feature and strength of this approach is its transparency in the process of factoring in uncertainty and reasoning about research findings. Subjective Logic promises to be a powerful complementary tool to incorporate uncertainty explicitly and transparently in the evaluation of research.