- Introduction: Doing Philosophy of Social Science
- Micro, Macro, and Mechanisms
- Mechanisms, Causal Modeling, and the Limitations of Traditional Multiple Regression
- Process Tracing and Causal Mechanisms
- Descriptive-Causal Generalizations: “Empirical Laws” in the Social Sciences?
- Useful Complex Causality
- Partial Explanations in Social Science
- Mechanistic Social Probability: How Individual Choices and Varying Circumstances Produce Stable Social Patterns
- The Impact of Duhemian Principles on Social Science Testing and Progress
- Philosophy and the Practice of Bayesian Statistics in the Social Sciences
- Sciences of Historical Tokens and Theoretical Types: History and the Social Sciences
- RCTs, Evidence, and Predicting Policy Effectiveness
- Bringing Context and Variability Back into Causal Analysis
- The Potential Value of Computational Models in Social Science Research
- Models of Culture
- The Evolutionary Program in Social Philosophy
- Cultural Evolution: Integration and Skepticism
- Coordination and the Foundations of Social Intelligence
- Making Race Out of Nothing: Psychologically Constrained Social Roles
- A Feminist Empirical and Integrative Approach in Political Science: Breaking Down the Glass Wall?
- Social Constructions of Mental Illness
- Cooperation and Reciprocity: Empirical Evidence and Normative Implications
- Evaluating Social Policy
- Values and the Science of Well-Being: A Recipe for Mixing
Abstract and Keywords
This article, which is concerned with counterfactuals insofar as they relate to causal inference about singular events, concentrates on counterfactuals that are closely connected to claims about actual causation. The claims about actual causation are important in the social sciences and the counterfactual approach to actual causation is a significant one, even if it is not universally valid. In David Lewis's account, the notion of natural law plays a crucial role. Social science counterfactuals sometimes involve backtracking. The article then introduces a (philosophical) theory of counterfactuals that makes use of causal modeling tools. Furthermore, the problems of circularity, backtracking, actual causation, and indeterminacy are the four problems that trouble the theory of counterfactuals. It is noted that the counterfactuals are useful for purposes other than causal inference. Counterfactual speculation may sometimes be the only way to make causal inferences about singular events.
Julian Reiss is associate professor in the philosophy faculty of Erasmus University Rotterdam, and specializes in philosophy of economics and general philosophy of science. Specific research interests are causal inference, measurement, models and thought experiments, and the place of values in science. Publications include Error in Economics: Towards a More Evidence-Based Methodology (Routledge, 2008), Causality Between Metaphysics and Methodology and Philosophy of Economics (both forthcoming with Routledge), and thirty-five papers in journals such as Philosophy of Science, Synthese, Philosophy of the Social Sciences, and Theoria.
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