The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes (...) in complex biological systems, I argue, have the property of enabling coherent causal control of these systems. Examples of such control variables include hormones and other signaling molecules, e.g., TOR (target of rapamycin), morphogens or the products of homeotic selector genes in embryonic pattern formation. I propose an analysis of this notion based on concepts borrowed from causal graph theory. (shrink)

In cases in which many causes together bring about an effect, it is common to select some as particularly important. Philosophers since Mill have been pessimistic about analyzing this reasoning because of its variability and the multifarious causal and pragmatic details of how it works. I argue Mill was right to think these details matter but wrong that they preclude philosophical analysis of causal selection. I show that analyzing the pragmatic details of scientific debates about the important causes of the (...) Bhopal Gas Tragedy can illuminate causal reasoning about disasters and shed new light on causality and causal selection. (shrink)

The concept of causal specificity is drawing considerable attention from philosophers of biology. It became the rationale for rejecting (and occasionally, accepting) a thesis of causal parity of developmental factors. This literature assumes that attributing specificity to causal relations is at least in principle a straightforward (if not systematic) task. However, the parity debate in philosophy of biology seems to be stuck at a point where it is not the biological details that will help move forward. In this paper, I (...) take a step back to reexamine the very idea of causal specificity and its intended role in the parity dispute in philosophy of biology. I contend that the idea of causal specificity across variations as currently discussed in the literature is irreducibly twofold in nature: it is about two independent components that are not mutually entailed. I show this to be the source of prior complications with the notion of specificity itself that ultimately affect the purposes for which it is often invoked, notably to settle the parity dispute. (shrink)

The epidemiologist Bradford Hill famously argued that in epidemiology, specificity of association (roughly, the fact that an environmental or behavioral risk factor is associated with just one or at most a few medical outcomes) is strong evidence of causation. Prominent epidemiologists have dismissed Hill’s claim on the ground that it relies on a dubious `one-cause one effect’ model of disease causation. The paper examines this methodological controversy, and argues that specificity considerations do have a useful role to play in causal (...) inference in epidemiology. More precisely, I argue that specificity considerations help solve a pervasive inferential problem in contemporary epidemiology: the problem of determining whether an exposure-outcome correlation might be due to confounding by a social factor. This examination of specificity has interesting consequences for our understanding of the methodology of epidemiology. It highlights how the methodology of epidemiology relies on local tools designed to address specific inference problems peculiar to the discipline, and shows that observational causal inference in epidemiology can proceed with little prior knowledge of the causal structure of the phenomenon investigated. I also argue that specificity of association cannot (despite claims to the contrary) be entirely explained in terms of Woodward’s well-known concept of “one-to-one” causal specificity. This is because specificity as understood by epidemiologists depends on whether an exposure (or outcome) is associated with a `heterogeneous’ set of variables. This dimension of heterogeneity is not captured in Woodward’s notion, but is crucial for understanding the evidential import of specificity of association. (shrink)

In recent years the notion of biological specificity has attracted significant philosophical attention. This paper focuses on host specificity, a kind of biological specificity that has not yet been discussed by philosophers, and which concerns the extent to which a species is selective in the range of other species it exploits for feeding and/or reproduction. Host specificity is an important notion in ecology, where it plays a variety of theoretical roles. Here I focus on the role of host specificity in (...) biological control, a field of applied ecology that deals with the suppression of pests through the use of living organisms. Examining host specificity and its role in biological control yields several valuable contributions to our understanding of biological specificity. In particular, I argue that host specificity cannot be fully understood in terms of Woodward’s well-known account of causal specificity. To adequately account for host specificity, we need a notion of causal specificity that takes into consideration the extent to which a variable’s effects are similar to one another – a dimension not captured in Woodward’s account. In addition, the literature on host specificity in biological control highlights certain aspects in which causally specific relationships can be practically valuable that have not yet been addressed in philosophical discussions of specificity. That literature also reveals that in certain contexts specificity can hinder rather than foster effective control, thus leading to a nuanced assessment of the practical value of specific causes. (shrink)

Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how (...) invariance could be qualified for such variables. (shrink)