This book, geared toward academic researchers and graduate students, brings together research on all facets of how time and causality relate across the sciences. Time is fundamental to how we perceive and reason about causes. It lets us immediately rule out the sound of a car crash as its cause. That a cause happens before its effect has been a core, and often unquestioned, part of how we describe causality. Research across disciplines shows that the relationship is much more complex than that. This book explores what that means for both the metaphysics and epistemology of causes - what they are and how we can find them. Across psychology, biology, and the social sciences, common themes emerge, suggesting that time plays a critical role in our understanding. The increasing availability of large time series datasets allows us to ask new questions about causality, necessitating new methods for modeling dynamic systems and incorporating mechanistic information into causal models.
|Publisher:||Cambridge University Press|
|Sold by:||Barnes & Noble|
|File size:||2 MB|
About the Author
Samantha Kleinberg is an Associate Professor of computer science at Stevens Institute of Technology, New Jersey. She received her Ph.D. in computer science from New York University, and previously held an NSF/CRA Computing Innovation Fellowship at Columbia University. She is the recipient of NSF CAREER and JSMF Complex Systems Scholar Awards and is a Kavli Fellow of the National Academy of Sciences. She is the author of Causality, Probability and Time (Cambridge, 2012) and Why: A Guide to Finding and Using Causes (2015).
Table of Contents1. An introduction to time and causality Samantha Kleinberg; 2. Causality and time: an introductory typology Bert Leuridan and Thomas Lodewyck; 3. The direction of causation Phil Dowe; 4. On the causal nature of time Victor Gijsbers; 5. Causation in a physical world: an overview of our emerging understanding Jenann Ismael; 6. Intervening in time Neil R. Bramely; 7. Time-event relationships as representations for constructing cell mechanisms Yin Chung Au; 8. Causation, time asymmetry, and causal mechanisms in the social sciences Inge de Bal and Erik Weber; 9. Temporalization in causal modeling Jonathan Livengood and Karen R. Zwier; 10. Reintroducing dynamics into static causal models Naftali Weinberger; 11. Overcoming the poverty of mechanisms in causal models David Jensen.