An intermediate representational framework to foster interdisciplinary communication: Discussing a future research line

Résumé

The behavioral and social sciences increasingly study similar problems in isolation. Researchers often use different concepts, measures, and disciplinary languages for structurally related situations, making it difficult to understand when we expect that findings will generalize across disciplinary topics, when disagreements are substantive, and when disciplines are simply talking past one another. This talk presents a possible future research line aimed at lowering these communication costs. Rather than discussing finished (empirical) results, I will use the talk to develop and discuss a set of somewhat tentative ideas. This talk will broadly consist of two parts. In the first, I’ll introduce my representational framework. This framework aims to provide an intermediate representational layer: a shared language, more explicit than ordinary prose but less demanding than full formal modeling, that we can use to systematically and explicitly describe decision situations across domains. In the second part, I’ll focus on a possible application for this framework. Specifically, my idea is to use reduced decision profiles, together with bibliometric analysis and large language models, to identify missed interdisciplinary connections between decision-making literatures.