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Session Submission Type: Full Paper Panel
Organized by Tasha Fairfield, London School of Economics
This panel brings together established professors and early career scholars to explore new ideas about probabilistic causal models, contingency, units of analysis, and hypothesis generation as relevant to process tracing and critical juncture analysis—two widely used methodological approaches in qualitative research and multi-method research more broadly.
The papers by Alan Jacobs & Macartan Humphreys and Hillel Soifer bring ideas developed outside the discipline of political science (computer science and quantitative geography respectively) to bear on the practice of process tracing. Similarly, the paper by Konrad Posch aims to integrate logical Bayesian (originated in the physical sciences) with classic typological theory in case study research. Meanwhile, the paper by Laura GarcĂa & James Mahoney presents a new set-theoretic, possible-worlds approach to defining contingent events.
We expect the panel to generate stimulating discussion on the relationship between inductive vs. deductive reasoning, the boundaries between probabilistic and deterministic causation, the nature of probability itself, case-level vs. population-level inference, the role of counterfactuals, and analytic transparency in qualitative research.
Process Tracing with Causal Models: Learning About Cases and Populations - Alan M. Jacobs, University of British Columbia; Macartan Humphreys, Columbia University
The Modifiable Areal Unit Problem and Process-Tracing in Case Study Research - Hillel David Soifer, Temple University
The Logic of Critical Juncture Analysis - James Mahoney, Northwestern University; Laura Garcia Montoya, Northwestern University
Bayesian Type Verification: Verifying Typologies with Logical Bayesianism - Konrad Posch, University of California, Berkeley