Non-reductive physicalists have long held that the special sciences offer explanations of some phenomena that are objectively superior to physical explanations. This explanatory “autonomy” has largely been based on the multiple realizability argument. Recently, in the face of the local reduction and disjunctive property responses to multiple realizability, some defenders of non-reductive physicalism have suggested that autonomy can be grounded merely in human cognitive limitations. In this paper, I argue that this is mistaken. By distinguishing between two kinds of abstraction (...) I show that the greater explanatory relevance of some special science predicates (to certain explananda) is both non-anthropocentric and not solely based on considerations of multiple realizability. This shows that the explanatory autonomy of the special sciences is safe from the local reduction and disjunctive property strategies, even if they are successful responses to the multiple realizability argument. (shrink)

Several philosophers (e.g., Ehring (Nous (Detroit, Mich.) 30:461–480, 1996 ); Funkhouser (Nous (Detroit, Mich.) 40:548–569, 2006 ); Walter (Canadian Journal of Philosophy 37:217–244, 2007 ) have argued that there are metaphysical differences between the determinable-determinate relation and the realization relation between mental and physical properties. Others have challenged this claim (e.g., Wilson (Philosophical Studies, 2009 ). In this paper, I argue that there are indeed such differences and propose a “mechanistic” account of realization that elucidates why these differences hold. This (...) account of realization incorporates two distinct roles that mechanisms play in the realization of mental (and other special science) properties which are implicit, but undeveloped, in the literature—what I call “constitutive” and “integrative” mechanisms. I then use these two notions of mechanism to clarify some debates about the relations between realization, multiple realizability, and irreducibility. (shrink)

A mechanistic explanation is a desired outcome in many studies of perception. Such explanations require discovering the processes that contribute to the realization of a perceptual phenomenon at different levels of information processing. The present analysis aims at investigating the obstacles to develop such mechanistic explanations and their potential solutions in the context of psychopathology. Geometric-Optical Illusions (GOIs) are among perceptual phenomena that have been studied to understand psychopathology in various clinical populations. In the present analysis, the GOIs will be (...) discussed as a methodological tool in the investigation of the mechanistic approach to understanding perception in such populations. I will argue that the fact that most such studies are mainly focused on the investigation of susceptibility to GOIs can only lead to classifying such phenomena or to reporting some correlations between different aspects of such phenomena with certain brain activities, without formulating a mechanistic explanation. The investigation of the variables that mediate perceptual phenomena at earlier stages of information processing is required for the formulation of such explanations. Thus, the objective of the present analysis is twofold: 1) showing how ignoring such variables have prevented the formulation of mechanistic explanations of responses to GOIs in clinical populations, such as schizophrenia and autism, 2) analyzing the methodological aspects of an effective approach in which a top-down guidance based on phenomenological insights (the first-person data) along with the insights provided by the existing theories help overcome obstacles in developing mechanistic explanations of GOIs. (shrink)

In this paper, reduction and its pragmatics are discussed in light of the development in computer science of languages to describe processes. The design of higher-level description languages within computer science has had the aim of allowing for description of the dynamics of processes in the (physical) world on a higher level avoiding all (physical) details of these processes. The higher description levels developed have dramatically increased the complexity of applications that came within reach. The pragmatic attitude of a (scientific) (...) practitioner in this area has become inherently anti-reductionist, but based on well-established reduction relations. The paper discusses how this perspective can be related to reduction in general, and to other domains where description of dynamics plays a main role, in particular, biological and cognitive domains. (shrink)