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Rethinking Explanation, Causality, and Prediction in Social Science
European Political Science Society Annual Meeting – 18-20 June 2026 – Belfast
UNIBO professors and CERSP Co-Directors, Matthew Loveless and Chiara Binelli, held a Standing-Room-Only panel titled, “Rethinking Explanation, Causality, and Prediction in Social Science’ [ME01] to bring together leading-edge thinking on empirical social science research and its direction.
Description: Across the social sciences, causality has become an organizing principle but also a polarizing force in research methodology. Entire research programs now pivot on identifying causal effects, which some argue has led to the expense of broader explanatory or theoretical ambitions. This panel brings together work that takes on these questions by pointing to novel ways of gaining credible, generalizable, and meaningful social inquiry. At the center lies a shared question: What does it mean to learn from data?
The papers approach this from different angles – rethinking how uncertainty can be measured and preregistered rather than merely controlled; how the accumulated record of studies might be reanalyzed to reveal generalizable patterns; how prediction can serve as a route to stronger theory rather than a substitute for it; and how the very concept of causality has drifted from a theoretical ideal into a methodological end in itself.
Taken together, these interventions suggest that methodological innovation is necessary to balance competing goals of research design. To move forward, these methods help make causality, prediction, and description as complementary methods that aim for the full explanation of complex human realities.
Pubblicato il: 05 luglio 2026
