Yafeng Wang

Process tracing method in the social sciences seek to assess hypothesized causal mechanisms in individual cases, but practitioners face a problem: How to use within-case evidence to evaluate singular causal relationships within hypothesized mechanism. This paper presents a partial solution to this problem by treating detailed features of the outcomes as observable consequences of the hypothesized causal relationships, given suitable auxiliary assumptions. This approach is then illustrated through analysis of a process-tracing study by Vesla Weaver. The paper concludes by examining how the feature-based approach relates to other frameworks for assessing singular causal claims.

It has been argued that non-epistemic values have legitimate roles to play in the classification of psychiatric disorders. Such a value-laden view on psychiatric classification raises questions about the extent to which expert disagreements over psychiatric classification are fueled by disagreements over value judgments and the extent to which these disagreements could be resolved. This paper addresses these questions by arguing for two theses. First, a major source of disagreements about psychiatric classification is factual and concerns what social consequences a classification decision will have. This type of disagreement can be addressed by empirical research, although obtaining and evaluating relevant empirical evidence often requires interdisciplinary collaboration. Second, there is also a type of disagreement over value judgments; namely, disagreements over which aims of psychiatric classification should be prioritized. To address this type of value disagreement, it is helpful to develop a plurality of different psychiatric classification systems, each targeted toward satisfying a different subset of stakeholder aims.

When a major engineering product failed, a failure investigation is often conducted to prevent similar failures in the future. In this dissertation, I propose an account of the epistemology and methodology of engineering failure investigations, based on a close examination of the documentations on five major plane crash investigations conducted by the National Transportation Safety Board (NTSB). The dissertation is divided into three parts. The first part consists of the five case studies arranged in chronological order: the American Airlines Flight 191 accident in 1979; the United Flight 232 accident in 1989; the United Flight 585 accident in 1991; the USAir Flight 427 accident in 1994; and the TWA Flight 800 accident in 1996. In each case study, I summarize the entire investigation process, focusing on articulating the questions that arise and the evidential reasoning that helped resolve each question. The second part of the dissertation examines how the investigators infer causes of failure events. The type of causal inference used in failure investigations typically proceeds from effects to causes, hence it is called reverse causal inference. This is in contrast with forward causal inference, where researchers start with an intervention and infer the effects of that intervention. I identify three types of reverse causal inference in engineering failure investigations: feature dependence, additional outcomes, and process tracing. The third part of the dissertation examines how the investigators construct narratives of failure events. At the end of each failure investigation, the investigators come up with a narrative detailing the sequence of events leading to the outcome. This part of the dissertation examines how the investigators construct such narratives and support them with evidence. I argue that both the construction and the justification of a narrative of a failure event depend on the question-and-answer process in the investigation, which I call the question dynamics of the investigation. I examine three main components of the question dynamics: the resolution of questions, the significance of questions, and the arising of questions. I conclude the dissertation with an account of the coherence of narratives, which is a measure of the evidential status of narratives. My account of coherence relies on the question dynamics, and it captures the intuitive idea that the pieces of a coherent narrative “fit together” very well.

Engineering accident investigations are systematic inquiries into the facts and causes of engineering accidents. The aims of an engineering accident investigation include identifying significant truths about an accident, learning lessons to prevent similar future accidents, and authoritatively communicating the investigative results to the stakeholders. An important normative dimension along which an engineering accident investigation can be evaluated is its degree of success in fulfilling these aims. In this paper, I propose criteria for evaluating the degree of success of an engineering accident investigation using a question-centered framework, and then argue for the relevance of this proposal to the actual engineering practice. The basic idea of my proposal is that an engineering accident investigation is successful to the extent that (1) questions that should arise in the investigation do arise, and (2) questions that arise—especially the more significant ones—are resolved satisfactorily by the end of the investigation. The first part of this paper unpacks my proposal by analyzing the following three concepts and illustrating them using examples from the TWA Flight 800 accident investigation: The (satisfactory) resolution of questions, the significance of questions, and the arising of questions. The second part of this paper argues for the relevance of my proposal to the practitioners and stakeholders of engineering accident investigations. First, I argue that my proposal is sensitive to the aims of the investigators and stakeholders regarding engineering accident investigations, and that it helps them navigate competing and conflicting aims. Second, I go beyond the TWA 800 case study and argue that my proposal explains the strengths and limitations of different types of accident causation models used in investigations.

Engineering failure investigations seek to reconstruct the actual causes of major engineering failures. The investigators need to establish the existence of certain past events and the actual causal relationships that these events bear to the failures in question. In this paper, I examine one method for reconstructing the actual causes of failure events, which I call "feature dependence". The basic idea of feature dependence is that some features of an event are informative about the features of its causes; therefore, the investigators can use the features of a known failure event to reconstruct details of its causes. I make explicit the structure of feature dependence and the evidential basis of its key premises, and show how feature dependence works in the investigation of the American Airlines Flight 191 accident.