Qualitative Counterfactual Analysis as a Method of Within-Case Analysis: The Case of Georgian Autocratic Backlash

Counterfactual reasoning is one of the oldest logics of causal inquiry and underpins a wide range of social-science methods, from comparative designs and process tracing to statistical and experimental approaches. Yet despite its ubiquity, counterfactual reasoning has rarely been formalised as a distinct qualitative method. Instead, it has remained either a philosophical assumption, a heuristic device, or an implicit component embedded within other methodological frameworks. This paper addresses this gap by developing Qualitative Counterfactual Analysis (QCfA) as a structured, transparent, and evidence-grounded method of within-case causal analysis. The paper argues that the long-standing scepticism toward counterfactuals stems not from their speculative nature per se, but from the absence of procedural rules linking counterfactual claims to empirical evidence. When alternative trajectories are reconstructed from observable continuities, stable structural constraints, and documented actor expectations, counterfactual reasoning becomes a disciplined form of causal inference rather than an intuitive or narrative exercise. Building on a realist ontology that treats political mechanisms as enduring causal dispositions operating within open systems, QCfA conceptualises causal analysis as the comparison between an observed trajectory and the nearest plausible counterfactual trajectory under conditions of conditional continuity. Methodologically, the paper specifies clear steps for reconstructing counterfactual paths, documenting assumptions, and subjecting alternative reconstructions to scrutiny through plausibility audits and transparency rules. The method is illustrated through an application to Georgia’s autocratic backlash following the war in Ukraine, showing how QCfA enables analysts to trace how external shocks recalibrate existing mechanisms rather than simply trigger discrete outcomes. By formalising counterfactual reasoning as a qualitative method, the paper contributes to strengthening causal inference in case-based research and clarifies the relationship between interpretation, mechanisms, and evidence.