From The Center for Empirical Philosophy and Behavioral Insights:
The Center for Empirical Philosophy and Behavioral Insights (CEPBI) is comprised of a group of researchers interested in the intersection of philosophy and behavioral science. More information can be found at http://www.cepbi.org/
We invite you to explore this intersection at our second 2025 online tandem talk titled “EXPERIMENTS, CAUSAL INFERENCE, AND LIMITS OF EVIDENCE” with:
- philosopher Nancy Cartwright (Durham University, UC San Diego),
- statistician Andrew Gelman (Columbia University), and
- behavioral scientist Berna Devezer (University of Idaho).
The online talk will take place on April 25 from 7:00-8:30 AM PT. You can join by Zoom here:
https://lmu-munich.zoom-x.de/j/65365292241?pwd=B9eJ4msJ9Epd704CvTawasuRrEjbaz.1https://lmu-munich.zoom-x.de/j/65365292241?pwd=B9eJ4msJ9Epd704CvTawasuRrEjbaz.1
About the talk:
In recent years, evidence from the behavioral sciences has come under intense scrutiny due to methodological concerns, particularly issues related to replicability. In this talk, we will explore the foundations and underlying causes of this criticism, challenge the uniformitarian assumptions often applied to behavioral evidence, and examine the limitations of experiments that seek to elicit law-like patterns in human behavior. We invite you to engage in a critical analysis of how knowledge is produced in disciplines that study humans both as subjects and as objects of the scientific process.
About the speakers:
Nancy investigates how scientific findings can meaningfully inform real-world decisions by centering her work on the methodology of the social sciences. She is interested in objectivity, causal inference, and the conditions under which evidence becomes actionable in fields like education, child protection, and international development.
Andrew examines how we use data to understand the world, with research spanning voter behavior, policy evaluation, toxicology, survey methods, and the interpretation of statistical effects. He is especially interested in the limits of inference and the practical challenges of applying statistical models to complex social questions.
Berna’s work focuses on reproducibility, statistical theory, and the modeling of scientific processes. Drawing from behavioral research and computational modeling, she explores how experimental design and research context shape the reliability and validity of empirical findings.