Petri Ylikoski

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations.

is chapter takes a fresh look at micro-macro relations in the social sciences from the point of view of the mechanistic account of explanation. Traditionally, micro- macro issues have been assimilated to the problem of methodological individualism. It is not my intention to resurrect this notoriously unfruitful controversy. On the contrary, the main thrust of this chapter is to show that the cul-de-sac of that debate can be avoided if we give up some of its presuppositions. The debate about methodological individualism is based on assumptions about explanation, and once we change those assumptions, the whole argumenta- tive landscape changes.

This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution is a synchronous and asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation.

In this paper I will discuss the idea of the invisible hand in the connection of its recent use in the philosophy of science. It has been invoked by some philosophers of science with a naturalistic bent as a part of their account of science. Some have made explicit references to the idea (Hull, 1988a) and others have only presupposed it (Giere, 1988; Goldman, 1991; Kitcher, 1993). I will argue that there are some problematic features in the way the idea of the invisible hand isused inthese accounts. I will first discuss some general properties of the invisible hand explanations and then present some motives for its use in the theory of science. Then I will show how one particular philosopher of science, David Hull, uses the idea. I will use Hull's account as a practising target and offer some comments and criticism in order to promote more disciplined use of this model of explanation in science studies.

This paper provides a conceptual analysis of the notion of interests as it is used in the social studies of science. After describing the theoretical background behind the Strong Program's adoption of the concept of interest, the paper outlines a reconstruction of the everyday notion of interest and argues that this same notion is used also by the sociologists of scientific knowledge. However, there are a couple of important differences between the everyday use of this notion and the way in which it used by the sociologists. The sociologists do not use the term in evaluative context and they do not regard interests as purely non-epistemic factors. Finally, it is argued that most of the usual critiques of interest explanations, by both philosophers and fellow sociologists, are misguided.

This article discusses agent-based simulation (ABS) as a tool of sociological understanding. I argue that agent-based simulations can play an important role in the expansion of explanatory understanding in the social sciences. The argument is based on an inferential account of understanding (Ylikoski 2009, Ylikoski & Kuorikoski 2010), according to which computer simulations increase our explanatory understanding by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. The inferential account also suggests a number of ways in which the use of simulation methodology might give rise to illusory understanding. The structure of the article is as ..

This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive explanations. Finally, the paper shows how the contrastive counterfactual theory of explanation can provide tools for assessing the explanatory power of models

This paper discusses Stephen Turner’s recent critique of theories of social practices. It shows that his arguments are valid against common explanatory uses of these concepts, but not against practices in general. There are plenty of legitimate non-explanatory uses for practice concepts. The paper also suggests that Turner’s main arguments derive from two principles that have much wider application than practice theories. Consequently, they should be considered as general constraints on every social theory.

This book is rather unorthodox in its composition. Instead of being a collection of essays, it consists of two series of debates between three writers. The first debate is between David Armstrong and U. T. Place, and consists of two contributions from both writers. The second debate is composed of C. B. Martin's essay "Properties and Dispositions," and two replies by each of the three authors. Although both debates are nominally about dispositions, they actually cover a wide array of questions that vary from causality to the universalia problem. This is natural, as the position taken on dispositions has consequences for views about causality, modality, laws of nature, and the ontology of properties, and vice versa. Probably the most important thing about the book is that it makes clear the central place dispositions have in ontology. This is a fact that has been forgotten all too often.

This work consists of two parts. Part I will be a contribution to a philo- sophical discussion of the nature of causal explanation. It will present my contrastive counterfactual theory of causal explanation and show how it can be used to deal with a number of problems facing theories of causal explanation. Part II is a contribution to a discussion of the na- ture of interest explanation in social studies of science. The aim is to help to resolve some controversies concerning interest explanation by explicating the concept of interest and its explanatory uses by using the account of explanation developed in Part I.

In this chapter I will employ a well-known scientific research heuristic that studies how something works by focusing on circumstances in which it does not work. Rather than trying to describe what scientific understanding would ideally look like, I will try to learn something about it by observing mundane cases where understanding is partly illusory. My main thesis is that scientists are prone to the illusion of depth of understanding (IDU), and as a consequence they sometimes overestimate the detail, coherence, and depth of their understanding. I will analyze the notion of understanding and its relation to a sense of understanding. In order to make plausible the claim that these are often disconnected, I will describe an interesting series of psychological experiments by Frank Keil and his coauthors that suggests that ordinary people routinely overestimate the depth of their understanding. en I will argue that we should take seriously the possibility that scientific cognition is also aðected by IDU and spell out some possible causes of explanatory illusions in science. I will conclude this chapter by discussing how scientific explanatory practices could be improved and how the philosophy of science might be able to contribute to this process.

Constitutivemechanisticexplanationsexplainapropertyofawholewith the properties of its parts and their organization. Carl Craver’s mutual manipulability criterion for constitutive relevance only captures the explanatory relevance of causal properties of parts and leaves the organization side of mechanistic explanation unaccounted for. We use the contrastive counterfactual theory of explanation and an account of the dimensions of organization to build a typology of organizational dependence. We analyse organizational explanations in terms of such dependencies and emphasize the importance of modular organizational motifs. We apply this framework to two cases from social science and systems biology, both fields in which organization plays a crucial explanatory role: agent-based simulations of residential segregation and the recent work on network motifs in transcription regulation networks.