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The Routledge Handbook of Causality and Causal Methods adopts a pluralistic, interdisciplinary approach to causality. It formulates distinct questions and problems of causality as they arise across scientific and policy fields.
List of contents
Introduction: The Mosaic of Causal Theory: Whence and Whither
Phyllis Illari and Federica Russo Part I: Causal Pluralism from Theory to Practice 1. The Plurality of Causal Pluralisms
Mariusz Maziarz 2. What Caused the COVID-19 Pandemic?
Trisha Greenhalgh, Eivind Engebretsen, and Tony Sandset Part II: Causal Theory and the Role of Researchers What is the variety of roles of the researchers (or groups of researchers) in the practices of causal discovery and validation? 3. Seeing Further: The Role of Modelers and Simulation in Causal Inference
Miles MacLeod 4. Causal Thinking in Global Health: Pragmatism and the Causal Mosaic
Erman Sözüdöru How is causality fundamental and/or practical in different disciplines? 5. Why Adoption of Causal Modeling Methods Requires Some Metaphysics
H.K. Andersen 6. The Physical Infrastructure Supporting Causal Cognition: Locality and Asymmetry
Mathias Frisch 7. Quiet Causation and its Many Uses in Science
Mauricio Suárez When are deeper ontological assumptions important and when are they not? 8. Causality in General Relativity (and Beyond): Heuristics from Metaphysics
Samuel C. Fletcher 9. Causation in Policy Science: Knowledge, Power, Meaning, Agency and Context
John Grin Part III: Features of Causal Systems Are there levels of causation? If so, what are they? 10. The Interplay Between Single-case and Generic Causation in Qualitative Social Science Research
Judith Schoonenboom 11. Causation Across Levels Throughout the Sciences
David Danks and Maralee Harrell 12. Social Causes and Epistemic (In)justice in Medical Machine Learning-mediated Medical Practices
Giorgia Pozzi and Juan M. Durán What are the boundaries of (causal) systems? How should we establish or cope with them? 13. How are (Causal) Systems Defined and How are Influences from Outside Dealt With?
Claus Beisbart 14. Individuation of Cross-Cutting Causal Systems in Cognitive Science and Behavioral Ecology
Marie I. Kaiser and Beate Krickel 15. Closure of Constraints and the Individuation of Causal Systems in Biology
Charbel N. El-Hani, Jeferson Gabriel da Encarnação Coutinho, and Clarissa Machado Pinto Leite What aspects of causal complexity are important and how are they handled in research? 16. The Challenge of Complexity: Causal Inference and Simulation Models in Macroeconomics
Alessio Moneta and Sebastiaan Tieleman 17. A Pluralistic (Mosaic) Approach to Causality in Health Complexity
Federica Russo, Alex Broadbent, Brian Castellani, Suzanne Fustolo-Gunnink, Naja Hulvej Rod, Morten Hulvej Rod, Spencer Moore, Harry Rutter, Karien Stronks, and Jeroen Uleman What are the challenges of causal cycles, and what are the best ways of meeting them? 18. Causal Cycles in Biology
William Bechtel and Andrew Bolhagen 19. Modelling Cyclic Causal Structures
Alexander Gebharter and Bert Leuridan Part IV: Causal Methods, Experimentation and Observation Under what circumstances is it (not) necessary to intervene experimentally? Or even to use non-experimental methods? 20. Physical vs Biomedical Sciences: Only the Latter Needs RCTs, but both Require Careful and Honest Methodology
Carl Hoefer 21. Non-experimental Interventions in Political Science and International Relations
Rosa Runhardt 22. Information Security, Intelligence Analysis, and Knowledge Generation without Experiments
Jonathan M. Spring and Phyllis Illari How is technology advancing or hindering causal reasoning? Or allowing increased epistemic access to causal relations? 23. Causality Problems in Machine Learning Systems
Alberto Termine and Giuseppe Primiero 24. Technology-driven Causal Inference: Prospects and Challenges
Dingmar van Eck and Kristian González Barman 25. The Combination of Brain Stimulation and Brain Imaging Technologies in the Cognitive Neurosciences: Problematizing the "Convergence Hypothesis"
Bas De Boer 26. Causal-manipulationist Approaches to Explaining Machine Learning
Juan M. Durán Part V: Measurement and Data What kind of metrics or measurement methods do causal methods need? 27. Causation and Realism: The Role of Instrumentally Mediated Empirical Evidence
Mahdi Khalili 28. Using Deep Neural Networks and Similarity Metrics to Predict and Control Brain Responses
Bojana Gruji¿i¿ and Phyllis Illari What is 'good quality' data for causal inference? 29. Between Quantity and Quality: Competing Views on the Role of Big Data for Causal Inference
Stefano Canali and Emanuele Ratti 30. Process Tracing with Qualitative Data
Julie Zahle Part VI: Causality, Knowledge, and Action What are the practices of causal explanation? 31. Moving Beyond Explanatory Monism
Melinda Bonnie Fagan 32. Comparing Prediction and Explanation in Computational Models: Theoretical Neuroscience vs. Language Technology
Marcin Mi¿kowski 33. Causal Mechanisms in the Social Sciences as Evidence for Higher-Order Causal Relations
Erik Weber 34. When Does an Event Become a Cause? Narrative Structure and Causal Indeterminacy
Paul A. Roth and John Beatty 35. Heterogeneous Causality: Levels of Causation and the WHOW Causal Logics in Qualitative Comparative Analysis
Sofia Pagliarin Do we need full knowledge of a system in order to establish causes? What can be done with partial knowledge? 36. When Decisions Must be Based on Partial Causal Knowledge: Analyzing Causality and Evidence for Health Policy
Fredrik Andersen, Rani Lill Anjum, and Elena Rocca 37. Going from Models to Action: Using Causal Knowledge for Everyday Choices
Samantha Kleinberg How is causal evidence to be used in regulatory contexts? 38. Evidence, Causation, Guidelines and Regulation: The Public Health Experience of NICE in England
Michael P. Kelly 39. Causal Evidence and the Social Determinants of Health: The Case of the Adverse Childhood Experiences Policies
Virginia Ghiara 40. Causation, Regulation, and the Assessment of Adverse Events Following Immunization (AEFIs)
Maria Laura Ilardo and Julian Reiss 41. Science to Policy Through Adverse Outcome Pathways
Annamaria Carusi 42. Causal Knowledge and the Process of Policy Making: Towards a Bottom-up Approach
Luis Mireles-Flores 43. From Evidence to Policy: Assessing Causal Claims in Nutrition Science
Saana Jukola Part VII: Causal Theory Across Disciplinary Borders How to theorise causality outside the canon? 44. Causality and Interdisciplinarity in the Philosophy of Science in Practice: The Cases of Ecology and Environmental Conservation
Luana Poliseli 45. What to Do When You Encounter Funky Causes in the (Historical) Wild
Eric Schliesser Where should we pioneer causal theory outside philosophical canon? 46. Clinical Reasoning as a Problem-solving Cognitive Activity: The Role of Causal Claims
Atocha Aliseda 47. Practical Causal Knowledge for Sustainability: Implications of Co-production for a Philosophical Understanding of Causality in Sustainability Science
Guido Caniglia and Maja Schlüter 48. Causality and Complex Systems in the Geosciences
Maarten G. Kleinhans How does causal theory make it into the classroom? 49. Causal Thinking in Science Education and the Challenges it Holds
Michal Haskel-Ittah 50. Causal Reasoning About Education: What is it and What Should it Be?
Arthur Bakker, Elisabeth Angerer, William R. Penuel, and Sanne F. Akkerman
About the author
Phyllis Illari is a Professor of Philosophy of Science in the Department of Science and Technology Studies at University College London. She has published extensively on causality, mechanisms, evidence, and information. With Federica Russo, she co-authored
Causality: Philosophical Theory Meets Scientific Practice (2014) and co-edited the
European Journal for Philosophy of Science for four years.
Federica Russo is a Professor of Philosophy and Ethics of Techno-Science and holds the Westerdijk Chair at the Freudenthal Institute, Utrecht University. She is the author of
Techno-Scientific Practices: An Informational Approach (2022),
Causality and Causal Modelling in the Social Sciences (2009). With Phyllis Illari, she co-authored
Causality: Philosophical Theory Meets Scientific Practice (2014) and co-edited the
European Journal for Philosophy of Science for four years.
Summary
The Routledge Handbook of Causality and Causal Methods adopts a pluralistic, interdisciplinary approach to causality. It formulates distinct questions and problems of causality as they arise across scientific and policy fields.
