The Cognitive Architecture of Preference Acquisition: Averageness, Typicality, and Valence

• Applicants: Dr. Moritz Ingendahl; Professor Dr. Tobias Vogel
• Subject Area: General, Cognitive and Mathematical Psychology ; Social Psychology, Industrial and Organisational Psychology
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 577261509

The main goal of the project is to investigate the mechanisms behind “Beauty-in-Averageness” (BiA) or prototype preference, a phenomenon in which people tend to prefer average exemplars of a category. The dominant explanation for this phenomenon is that average exemplars are easier to process. However, our own research shows that average exemplars also tend to inherit core category attributes, including the category's valence. This results in a reversed BiA effect for negative categories—a finding that contradicts the fluency explanation. Building on this knowledge, we aim to develop and test a new model called "AVerageness and Valence In CATegories (AVICAT)". This model integrates our previous category valence account with research on categorization and sampling. The model allows for precise predictions about when different types of category exemplars will be preferred, depending on category structure, category valence, and experience with the category. The project is divided into three work packages: 1. Influence of Category Valence on BiA: This package investigates the specific cognitive processes by which category valence impacts BiA. Three possible processes will be tested across three experiments. 2. Distinction between Averageness and Typicality: The model differentiates between “average” and “typical.” While averageness is often perceived as typical, categorization research has revealed situations in which this does not apply. This work package identifies three such boundary conditions where averageness thus leads to weaker effects of category valence—and thereby to "normal" BiA effects in negative categories. This will be tested in three experiments. 3. Influence of Sampling: This package explores how BiA effects can arise in natural environments where people proactively sample positive categories more frequently than negative ones. The model enables precise predictions, including potentially opposing preferences compared to restricted environments where sampling is not possible. This will be tested in three experiments.

• DFG Programme: Research Grants
• International Connection: USA
• Cooperation Partner: Professor Dr. Piotr Winkielman