This article addresses the contributions of the literature on the new mechanistic philosophy of science for the scientific practice of model building in ecology. This is reflected in a one-to-one interdisciplinary collaboration between an ecologist and a philosopher of science during science-in-the-making. We argue that the identification, reconstruction and understanding of mechanisms is context-sensitive, and for this case study mechanistic modeling did not present a normative role but a heuristic one. We expect our study to provides useful epistemic tools for (...) the improvement of empirically-riven work in the debates about mechanistic explanation of ecological phenomena. (shrink)

This article considers interventionist arguments for downward causation and non-fundamental level causal explanation from the point of view of inferring causation from experiments. Several authors have utilised the interventionist theory of causal explanation to argue that the causal exclusion argument is moot and that higher-level as well as downward causation is real. I show that this argument can be made when levels are understood as levels of grain, leaving us with a choice between causal explanations pitched at different levels. Causal (...) proportionality has been suggested as a principle for choosing the correct level of description for causal explanations, but this suggestion has serious problems. I offer an alternative principle, based on the idea that explanations should track actual difference-makers. I then consider claims about systems causally influencing their own parts. Such claims risk conceptual confusion for the same reason as the exclusion argument, by conflating causal and constitutive dependencies. The distinction between causation and constitution is used to give criteria for the correct use of the idea of downward causation. (shrink)

The interventionist account of causal explanation, in the version presented by Jim Woodward, has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as presently (...) formulated it is either unable to prefer high-level explanations to low, or systematically overshoots, recommending explanations at so high of a level as to be virtually vacuous. (shrink)

Currently, there are almost as many conceptions of emergence as authors who address the issue. Most literature on the matter focuses either on discussing, evaluating and comparing particular contributions or accounts of emergence, or on assessing a particular case study. Our aim in this paper is rather different. We here set out to introduce a distinction that has not been sufficiently taken into account in previous discussions on this topic: the distinction between inter-domain emergence—a relation between items belonging to different (...) ontic domains—and intra-domain emergence—a relation between items belonging to a same ontic domain. Our final purpose is not to assume and defend a definite stance on emergence, but to stress the relevance of such distinction when attempting to argue for or against emergence, in the first place. We will also address the connections between emergence so distinguished and more general philosophical perspectives, suggesting where would reductionists and pluralists stand with respect to intra- and inter-domain emergence. (shrink)

Despite the ubiquity of “levels of organization” in the scientific literature, a nascent “levels skepticism” now claims that the concept of levels is an inherently flawed, misleading, or otherwise inadequate notion for understanding how life scientists produce knowledge about the natural world. However, levels skeptics rely on the maligned “layer-cake” account of levels stemming from Oppenheim and Putnam’s defense of the unity of science for their critical commentary. Recourse to layer-cake levels is understandable, as it is arguably the default conception (...) of levels in philosophy. However, relying on this conception of levels undermines the initial plausibility of general dismissals of the concept, because the problems skeptics identify within the “basic idea” of the concept “levels” are merely ones already widely acknowledged in this conception. I illustrate this “guilt by association” by looking at the embedded role of “levels” in articulating intertheoretical reductionism during the latter part of the 20th century. I conclude by suggesting a methodological framework focusing on local usage patterns as a promising means for future analysis of the levels concept. (shrink)

Much recent work on explanation in the interventionist tradition emphasizes the explanatory value of stable causal generalizations—i.e., causal generalizations that remain true in a wide range of background circumstances. We argue that two separate explanatory virtues are lumped together under the heading of `stability’. We call these two virtues breadth and guidance respectively. In our view, these two virtues are importantly distinct, but this fact is neglected or at least under-appreciated in the literature on stability. We argue that an adequate (...) theory of explanatory goodness should recognize breadth and guidance as distinct virtues, as breadth and guidance track different ideals of explanation, satisfy different cognitive and pragmatic ends, and play different theoretical roles in helping us understand the explanatory value of mechanisms. Thus keeping track of the distinction between these two forms of stability yields a more accurate and perspicuous picture of the role that stability considerations play in explanation. (shrink)

The philosophical discussion of emergence is often focused on properties of ‘wholes’ that are evaluated as emergent with respect to the properties of ‘parts’. Downward causation is, consequently, evaluated as some kind of causal influence of whole properties over parts properties. Yet, several important cases in scientific practice seem to be pursuing hypotheses of parts properties emerging from wholes properties, inverting the instinctive association of emergence with wholes. Furthermore, some areas of reflection which are very important for emergence, e.g., the (...) philosophy of consciousness, do not allow mapping properties onto part-whole organizations. The conceptual puzzle is solved by constructing a framework that disentangles the mereological dimension from the superventional dimension. By liberalizing the spatio-temporal allocation of emergent properties, the proposed dual framework could better capture the way in which emergence and downward causation are addressed in scientific practice. (shrink)

This dissertation aims to determine the optimal level of granularity for the variables used in probabilistic causal models. These causal models are useful for generating explanations in a number of scientific contexts. In Chapter 1, I argue that there is rarely a unique level of granularity at which a given phenomenon can be causally explained, thereby rejecting various causal exclusion arguments. In Chapter 2, I consider several recent proposals for measuring the explanatory power of causal explanations, and show that these (...) measures fail to track the comparative depth of explanations given at different levels of granularity. In Chapter 3, I offer a pragmatic account of how to partition the measure space of a causal variable so as to optimally explain its effect. My account uses the decision-theoretic notion of value of information, and indexes the relative depth of an explanation to a particular agent faced with a particular decision problem. Chapter 4 applies this same decisiontheoretic framework to answer the epistemic question of how to discover constitutive relationships in nature. In Chapter 5, I describe the formal details of the relationship between random variables that are meant to be coarse-grained and fine-grained representations of the same type of phenomenon. I use this formal framework to rebut a popular argument for the view that special science probabilities can be objective chances. Chapter 6 discusses challenges related to the causal interpretation of Bayes nets that use imprecise rather than precise probabilities. (shrink)