Machamer, Darden, and Craver argue that causal explanations explain effects by describing the operations of the mechanisms which produce them. One of this paper’s aims is to take advantage of neglected resources of Mechanism to rethink the traditional idea that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal explanations. I think that causal productivity and regularity are by no means the same thing, (...) and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers’ from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research. (shrink)

Scientists obtain a great deal of the evidence they use by observingnatural and experimentally generated objects and effects. Much of thestandard philosophical literature on this subject comes from20th century logical positivists and empiricists, theirfollowers, and critics who embraced their issues and accepted some oftheir assumptions even as they objected to specific views. Theirdiscussions of observational evidence tend to focus on epistemologicalquestions about its role in theory testing. This entry follows theirlead even though observational evidence also plays important andphilosophically interesting roles (...) in other areas including scientificdiscovery and the application of scientific theories to practicalproblems. (shrink)

This paper suggests and discusses an answer to the following question: What distinguishes causal from non-causal or coincidental co-occurrences? The answer derives from Elizabeth Anscombe’s idea that causality is a highly abstract concept whose meaning derives from our understanding of specific causally productive activities, and from her rejection of the assumption that causality can be informatively understood in terms of actual or counterfactual regularities.Keywords: Elizabeth Anscombe; Causality; Explanation; Inhibition.

Using Jim Woodward's Counterfactual Dependency account as an example, I argue that causal claims about indeterministic systems cannot be satisfactorily analysed as including counterfactual conditionals among their truth conditions because the counterfactuals such accounts must appeal to need not have truth values. Where this happens, counterfactual analyses transform true causal claims into expressions which are not true.

Standard philosophical discussions of theory-ladeness assume that observational evidence consists of perceptual outputs (or reports of such outputs) that are sentential or propositional in structure. Theory-ladeness is conceptualized as having to do with logical or semantical relationships between such outputs or reports and background theories held by observers. Using the recent debate between Fodor and Churchland as a point of departure, we propose an alternative picture in which much of what serves as evidence in science is not perceptual outputs or (...) reports of such outputs and is not sentential in structure. (shrink)

Empiricists claim that in accepting a scientific theory one should not commit oneself to claims about things that are not observable in the sense of registering on human perceptual systems (according to Van Fraassen’s constructive empiricism) or experimental equipment (according to what I call liberal empiricism ). They also claim scientific theories should be accepted or rejected on the basis of how well they save the phenomena in the sense delivering unified descriptions of natural regularities among things that meet their (...) conditions for observability. I argue that empiricism is both unfaithful to real world scientific practice, and epistemically imprudent, if not incoherent. To illuminate scientific practice and save regularity phenomena one must commit oneself to claims about causal mechanisms that can be detected from data, but do not register directly on human perceptual systems or experimental equipment. I conclude by suggesting that empiricists should relax their standards for acceptable beliefs. (shrink)

Some biological processes move from step to step in a way that cannot be completely understood solely in terms of causes and correlations. This paper develops a notion of mechanistic information that can be used to explain the continuities of such processes. We compare them to processes that do not involve information. We compare our conception of mechanistic information to some familiar notions including Crick’s idea of genetic information, Shannon-Weaver information, and Millikan’s biosemantic information.

I claim that the Hodgkin‐Huxley (HH) current equations owe a great deal of their importance to their role in bringing results from experiments on squid giant action preparations to bear on the study of the action potential in other neurons in other in vitro and in vivo environments. I consider ideas from Weber and Craver about the role of Coulomb’s and other fundamental equations in explaining the action potential and in HH’s development of their equations. Also, I offer an embellishment (...) to Schaffner’s emergent unifier conception of the HH model. †To contact the author, please write to: Department of HPS, University of Pittsburgh, 1017 Cathedral of Learning, Pittsburgh, PA 15260; e‐mail: [email protected]. (shrink)

This essay uses Györgi Buzsáki's use of EEG data to draw conclusions about brain function as an example to show that investigators sometimes draw conclusions from noisy data by analyzing the noise rather than by extracting a signal from it. The example makes vivid some important differences between McAllister's, Woodward's, and my ideas about how data are interpreted.

Familiar versions of empiricism overemphasize and misconstrue the importance of perceptual experience. I discuss their main shortcomings and sketch an alternative framework for thinking about how human sensory systems contribute to scientific knowledge.

According to a received doctrine, espoused, by Karl Popper and Harry Collins, and taken for granted by many others, poorly replicated evidence should be epistemically defective and incapable of persuading scientists to accept the views it is used to argue for. But John Hughlings Jackson used poorly replicated clinical and post-mortem evidence to mount rationally compelling and influential arguments for a highly progressive theory of the organization of the brain and its functions. This paper sets out a number of Jackson's (...) arguments from his evidence and argues that they constitute a counter example against the received doctrine. (shrink)

This paper compares the relative merits of two alternatives to traditional accounts of causal explanation: Jim Woodward's counterfactual invariance account, and the Mechanistic account of Machamer, Darden, and Craver. Mechanism wins (a) because we have good causal explanations for chaotic effects whose production does not exhibit the counterfactual regularities Woodward requires, and (b)because arguments suggested by Belnap's and Green's discussion of prediction (in'Facing the Future' chpt 6)show that the relevant counterfactuals about ideal interventions on non-deterministic and deterministic systems lack truth (...) value. (shrink)