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To study people's processing of hurricane forecast advisories, we conducted a computer‐based experiment that examined 11 research questions about the information seeking patterns of students assuming the role of a county emergency manager in a sequence of six hurricane forecast advisories for each of four different hurricanes. The results show that participants considered a variety of different sources of information—textual, graphic, and numeric—when tracking hurricanes. Click counts and click durations generally gave the same results but there were some significant differences. Moreover, participants' information search strategies became more efficient over forecast advisories and with increased experience tracking the four hurricanes. These changes in the search patterns from the first to the fourth hurricane suggest that the presentation of abstract principles in a training manual was not sufficient for them to learn how to track hurricanes efficiently but they were able to significantly improve their search efficiency with a modest amount (roughly an hour) of practice. Overall, these data indicate that information search patterns are complex and deserve greater attention in studies of dynamic decision tasks.

This article offers a process-mechanism explanation of securitization. To make the case for a process-mechanism account more concrete, I use interpretivist process tracing to explain the crisis episode of the Sun Sea, a Thai cargo ship carrying Sri Lankan asylum-seekers, and the securitization of irregular migration in Canada. Drawing on interviews and grey literature, the article shows how securitization was possible and under what conditions, and argues that ideational dispositions of security organizations induced state officials toward a security interpretation of the the Sun Sea. The article aims to demonstrate that process-mechanism explanations represent a compelling methodological alternative with which to trace and explain securitization. The article sees itself as part of a broader refinement of a sociological variant of securitization theory. It seeks to examine and enhance the contribution that this 'post-Copenhagen' approach – its core assumptions and theoretical framework – makes to the analysis of securitization.

Commissioners of impact evaluation often place great emphasis on assessing the contribution made by a particular intervention in achieving one or more outcomes, commonly referred to as a 'contribution claim'. Current theory-based approaches fail to provide evaluators with guidance on how to collect data and assess how strongly or weakly such data support contribution claims. This article presents a rigorous quali-quantitative approach to establish the validity of contribution claims in impact evaluation, with explicit criteria to guide evaluators in data collection and in measuring confidence in their findings. Coined 'Contribution Tracing', the approach is inspired by the principles of Process Tracing and Bayesian Updating, and attempts to make these accessible, relevant and applicable by evaluators. The Contribution Tracing approach, aided by a symbolic 'contribution trial', adds value to impact evaluation theory-based approaches by: reducing confirmation bias; improving the conceptual clarity and precision of theories of change; providing more transparency and predictability to data-collection efforts; and ultimately increasing the internal validity and credibility of evaluation findings, namely of qualitative statements. The approach is demonstrated in the impact evaluation of the Universal Health Care campaign, an advocacy campaign aimed at influencing health policy in Ghana.

Bayesian probability holds the potential to serve as an important bridge between qualitative and quantitative methodology. Yet whereas Bayesian statistical techniques have been successfully elaborated for quantitative research, applying Bayesian probability to qualitative research remains an open frontier. This paper advances the burgeoning literature on Bayesian process tracing by drawing on expositions of Bayesian "probability as extended logic" from the physical sciences, where probabilities represent rational degrees of belief in propositions given the inevitably limited information we possess. We provide step-by-step guidelines for explicit Bayesian process tracing, calling attention to technical points that have been overlooked or inadequately addressed, and we illustrate how to apply this approach with the first systematic application to a case study that draws on multiple pieces of detailed evidence. While we caution that efforts to explicitly apply Bayesian learning in qualitative social science will inevitably run up against the difficulty that probabilities cannot be unambiguously specified, we nevertheless envision important roles for explicit Bayesian analysis in pinpointing the locus of contention when scholars disagree on inferences, and in training intuition to follow Bayesian probability more systematically.

This article explores the practical challenges one faces when combining Qualitative Comparative Analysis (QCA) and Process-tracing (PT) in a manner that is consistent with their underlying assumptions about the nature of causal relationships. While PT builds on a mechanism-based understanding of causation, QCA as a comparative method makes claims about counterfactual causal relationships. The consequence of this is that the analyst is forced to choose whether to be more in alignment with one or the other method. The article proceeds in four steps, exploring the challenges and opportunities resulting from two different understandings of causation underlying QCA and PT. The article first presents the research area used to explore the practical challenges of combining the two methods. I investigate the causes of congruence between what voters want and government positions in EU constitutional negotiations, part of the broader phenomenon of the representation of voter views in public policies. The section develops a range of potential causes for congruence from the existing literature. Second, using a QCA-first design I undertake a fsQCA analysis of sufficiency. Utilized in a theory-building fashion, I investigate whether the potential causes identified in the literature form conjunctions of conditions that are together sufficient to produce congruence between voter views and governmental positions. The article only finds one conjunction that is robust: the combination of PR systems and the EU being a highly salient issue in domestic politics (electoral connection). Third, the article engages in a PT case study of two positive cases of the electoral connection conjunction. At the theoretical level, gaming through a causal mechanism for the conjunction suggests that one of the two terms should better be understood as a scope instead of causal condition, providing a better theoretical understanding of the found conjunction. Issues of case selection are then discussed, finding that a restrictive policy in alignment with QCA tenets results in some promising potential cases being rejected. The actual case studies find some evidence for the presence of the hypothesized mechanism, although when we select a case where another conjunction is also present (referendum), there is stronger evidence for the referendum than electoral connection conjunction. Finally, the conclusion discusses the methodological lessons learned in practice, focusing on the need to justify case selection in terms of whether one is more in alignment with either QCA or PT, and the need to make conclusions that are consistent with the types of inferences made possible by PT case studies, i.e. a mechanism produced by a conjunction is either present or not in a case, with no claims made about its necessity or sufficiency.