1st Edition
The Routledge Handbook of Causality and Causal Methods
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. Exploring, in a comparative way, how these questions and problems are addressed in different areas, the Handbook fosters dialogue and exchange. It emphasizes the role of the researchers and the normative considerations that arise in the development of methodological and empirical approaches. The Handbook includes authors from all over the world and with many different disciplinary backgrounds, and its 51 chapters appear in print here for the first time. The chapters are organized into the following seven parts:
I. Causal Pluralism, from Theory to Practice
II. Causal Theory and the Role of Researchers
III. Features of Causal Systems
IV. Causal methods, Experimentation and Observation
V. Measurement and Data
VI. Causality, Knowledge, and Action
VII. Causal Theory across Disciplinary Borders
Essential reading for scholars interested in an interdisciplinary approach to causality and causal methods, the volume is also a valuable resource for advanced undergraduates as well as for graduate students interested in delving into the rich field of causality.
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 Sözüdoğru
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 Grujičić 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 Miłkowski
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
Biography
Phyllis Illari is 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 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.
