Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Doctor of Philosophy

Program

Philosophy

Supervisor

Wayne C. Myrvold

Abstract

The past century has witnessed numerous methodological innovations in probabilistic and statistical methods of causal inference (e.g., the graphical modelling and the potential outcomes frameworks, as introduced in Chapter 1). These innovations have not only enhanced the methodologies by which scientists across diverse domains make causal inference, but they have also made a profound impact on the way philosophers think about causation. The philosophical issues discussed in this thesis are stimulated and inspired by these methodological innovations.

Chapter 2 addresses the question of how the holding of screening-off conditions for a causal model depends on the choice of variables. As bridge principles between probability and causation, screening-off conditions (especially the Causal Markov Condition) play a key role in causal inference. However, it has been known that these conditions may fail due to poor variable choice. My aim in this chapter is to further examine those constraints on variable choice that are deemed necessary for the satisfaction of screening-off conditions.

The idea of a well-defined (hypothetical) intervention is also crucial for reliable causal inference. Chapter 3 explores the question of when interventions invoked in causal inference are “well-defined” or unambiguous, and how this requirement constrains the choice of cause-variables. I propose that an intervention is well-defined just in case the effect of interest is well-defined (under ideal interventions), and that the intervention can serve as a suitable means to identify that effect. Based on this proposal, several distinct types of ambiguous interventions are identified.

Methodological progress in causal inference also poses the following question: Can such progress shed light on the ontology of causation? My answer is yes. In Chapter 4, I develop a Carnapian-pragmatist approach to the ontology of causation as an alternative to existing metaphysical approaches. I argue that, compared to traditional metaphysics, the pragmatist approach provides a superior picture of how the ontology and methodology of causation interact with each other in scientific practice.

I conclude in Chapter 5 that the thing we call “causation” consists in both the right worldly infrastructure (e.g., screening-off patterns and possibilities for interventions) and appropriate ways of framing this infrastructure.

Summary for Lay Audience

Given the importance of causal reasoning in everyday life and science, it is little wonder that causation has drawn so much attention from philosophers. Recent developments in (statistical) methods of causal inference (e.g., graphical causal modelling) have further fuelled philosophical discussions on this perennial topic. Inspired by these methods, this thesis explores a few closely related philosophical questions.

First, consider the intuitive idea—which plays a key role in causal inference—that if two events or variables are correlated but neither causes the other, then they must share a common cause which can explain away or “screen off” the correlation. This principle is known to be fallible: when the variables in question are poorly chosen, a common cause may not screen off the effect variables. So, the first question the thesis addresses is: When are variables suitable for screening-off?

Consider another important idea in causal inference, namely, a variable causes another variable just means that if we could (hypothetically) manipulate or wiggle the cause-variable, the effect-variable would change accordingly. However, sometimes a manipulation may be ambiguous, meaning that the outcome of the manipulation is indeterminate. Again, the choice of variables matters: some variables do not seem to support well-defined manipulations (e.g., race). So, the second question I address in this thesis is: What kind of variables can afford well-defined manipulations?

Both of the above questions are primarily concerned with the methodology of causal inference, but what about the reality or ontology of causation? Traditionally, metaphysicians have divided themselves into two camps on this question: causal reductionists (who argue that ultimately there is no such thing as causation) and anti-reductionists (who argue against reductionists). However, in this thesis, I contend that both metaphysical approaches are deeply flawed. Drawing upon inspiration from Rudolf Carnap, I advocate a pragmatist alternative to the ontology of causation.

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