What is "context", and how can we best test for its influence (or the lack thereof)? The diversity in settings covered by the literature on contextual influences, spanning from low-level foraging tasks in amoeboid organisms to real-world market behavior, goes hand-in-hand with an almost equal diversity of testing approaches designed to assess the presence of context effects. Are all these studies testing the same concept of "context"? How do the design decisions relate to the theoretical framework that is being subjected to the test? The present project aims to clarify these questions and provide guidelines on which experimental designs are most suitable for testing specific theoretical properties.

In the talk, I will critically evaluate the three pillars of testing for context effects, the conceptual, measurement, and empirical pillars. The conceptual pillar provides the definition of a "context effect" by means of a benchmark property. That is, a behavioral property that, when empirically violated, establishes the presence of a context effect. The measurement pillar translates the benchmark properties into measurement models that allow to quantify the degree of (mis)match between concepts and data. The empirical pillar establishes an experimental design in which different choice scenarios are to be taken as distinct contexts. I will demonstrate that different experimental designs vary dramatically in their ability to establish the presence of a context effect. Finally, I will report a reanalysis of published data and argue that more fine-grained analyses using individual-level classifications are crucial to properly link observed behavior to its theoretical foundations.

Zoom Invitation Link

Meeting ID: 929 8732 1245

Passcode: 135374