Robert Northcott

I use a contrastive theory of causal explanation to analyze the notion of a genetic trait. The resulting definition is relational, an implication of which is that no trait is genetic always and everywhere. Rather, every trait may be either genetic or non-genetic, depending on explanatory context. I also outline some other advantages of connecting the debate to the wider causation literature, including how that yields us an account of the distinction between genetic traits and genetic dispositions.

Election prediction by means of opinion polling is a rare empirical success story for social science. I examine the details of a prominent case, drawing two lessons of more general interest: Methodology over metaphysics. Traditional metaphysical criteria were not a useful guide to whether successful prediction would be possible; instead, the crucial thing was selecting an effective methodology. Which methodology? Success required sophisticated use of case-specific evidence from opinion polling. The pursuit of explanations via general theory or causal mechanisms, by contrast, turned out to be precisely the wrong path—contrary to much recent philosophy of social science

The causal impacts of genes and environment on any one biological trait are inextricably entangled, and consequently it is widely accepted that it makes no sense in singleton cases to privilege either factor for particular credit. On the other hand, at a population level it may well be the case that one of the factors is responsible for more variation than the other. Standard methodological practice in biology uses the statistical technique of analysis of variance to measure this latter kind of causal efficacy. In this paper, I argue that: 1) analysis of variance is in fact badly suited to this role; and.

The 1994 US spectrum auction is now a paradigmatic case of the successful use of microeconomic theory for policy-making. We use a detailed analysis of it to review standard accounts in philosophy of science of how idealized models are connected to messy reality. We show that in order to understand what made the design of the spectrum auction successful, a new such account is required, and we present it here. Of especial interest is the light this sheds on the issue of progress in economics. In particular, it enables us to get clear on exactly what has been progressing, and on exactly what theory has – and has not – contributed to that. This in turn has important implications for just what it is about economic theory that we should value.

I present a new definition of verisimilitude, framed in terms of causes. Roughly speaking, according to it a scientific model is approximately true if it captures accurately the strengths of the causes present in any given situation. Against much of the literature, I argue that any satisfactory account of verisimilitude must inevitably restrict its judgments to context-specific models rather than general theories. We may still endorse—and only need—a relativized notion of scientific progress, understood now not as global advance but rather as the mastering of particular problems. This also sheds new light on longstanding difficulties surrounding language-dependence and models committed to false ontologies.

Although a huge range of definitions has accumulated in the philosophy, biology and psychology literatures, no consensus has been reached on exactly what innateness amounts to. This has helped fuel an increasing skepticism, one that views the concept as anachronistic and actually harmful to science. Yet it remains central to many life sciences, and to several public policy issues too. So it is correspondingly urgent that its philosophical underpinnings be properly cleaned up. In this paper, I present a new approach that endorses a role in science for innateness while also accommodating many of the skeptical concerns. The key to squaring the circle is to import influential recent work on causal explanation. My thesis is that ascriptions of innateness are best seen as explanatory claims. The account that results has three main original features: 1) Innateness is a pragmatic, relational concept. Every trait may be either innate or non-innate, depending on explanatory context. 2) There is an important distinction between innate traits and innate dispositions. 3) Innateness is useful to science as a higher-level predicate that licenses interventions. It is thereby also clarified what ascriptions of innateness do not tell us.