Petri Ylikoski

Explanatory relevance across disciplinary boundaries: the case of neuroeconomics

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.

Generative Explanation and Individualism in Agent-Based Simulation

Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.

Agent-Based Simulation and Sociological Understanding

The article discusses agent-based simulation as a tool of sociological understanding. Based on an inferential account of understanding, it argues that computer simulations increase our explanatory understanding both by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. However, our ability to understand simulations limits our ability to understand real world phenomena through them. Thomas Schellings checkerboard model of ethnic segregation is used to demonstrate the important role played by abstract how-possibly models in the process of building a mechanistic understanding of social phenomena.

How Organization Explains

Constitutive mechanistic explanations explain a property of a whole with 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.

Comment on Naturalizing Critical Realist Social Ontology

Abstract This comment discusses Kaidesoja (2013) and raises the issue whether his analysis justifies stronger conclusions than he presents in the book. My comments focus on four issues. First, I argue that his naturalistic reconstruction of critical realist transcendental arguments shows that transcendental arguments should be treated as a rare curiosity rather than a general argumentative strategy. Second, I suggest that Kaidesoja’s analysis does not really justify his optimism about the usefulness of causal powers ontology in the social sciences. Third, I raise some doubts about the heuristic value of Mario Bunge’s social ontology that Kaidesoja presents as a replacement for critical realist ontology. Finally, I propose an alternative way to analyze failures of aggregativity that might better serve Kaidesoja’s purposes than the Wimsattian scheme he employs in the book.

Rethinking Micro-Macro Relations

This paper proposes a new approach to the micro-macro problem in the social sciences. It argues that the common strategy of borrowing arguments from the philosophy of mind debates is not fruitful and the micro-macro relations should not be conceptualized in terms of ‘levels’. This way of thinking is systematically misleading and fails to provide methodologically useful guidance. As a replacement the paper suggests an approach that consider micro-macro relations in terms of scale. In this view there is no unique micro level in the social sciences, and the micro-macro contrast is always context-relative. When combined with the idea of mechanism-based explanation this idea provides an effective tool for thinking about explanation-related controversies in the philosophy of social sciences. For example, by clearly distinguishing causal and constitutive explanations at different scales, it is possible to resolve many conceptual puzzles related to macro causation. The scale-based approach also makes it possible to explore the diversity of macro social properties. To emphasize the importance of this diversity, the paper concludes by presenting a fourfold classification of these properties.

Neural Network Templates and Their Interpretation

The wide applicability of neural networks poses an interesting challenge for the philosophy of science. This paper argues that when used for explanatory purposes, the interpretation of the neural networks computational template is crucial. The dynamics of debate about the interpretation of a model are illustrated with examples from the recent history of the neurocognitive sciences.

Three Conceptions of a Theory of Institutions

We compare Guala’s unified theory of institutions with that of Searle and Greif. We show that unification can be many things and it may be associated with diverse explanatory goals. We also highlight some of the important shortcomings of Guala’s account: it does not capture all social institutions, its ability to bridge social ontology and game theory is based on a problematic interpretation of the type-token distinction, and its ability to make social ontology useful for social sciences is hindered by Guala’s interpretation of social institution types as social kinds akin to natural kinds.

Review of Process-Tracing Methods: Foundations and Guidelines, by Derek Beach and Rasmus Brun Pedersen

tal problems. Weszkalnys and Barry show how ambitions to create new interdisciplinary research institutions accountable to the public played out very differently in different settings. Not only did different national traditions provide different organizational possibilities, but these differences were incorporated differently into the organization and knowledge production of the institution. Academic publication becomes a hard measure for public accountability for all three institutions, but other kinds of outreach or contributions to the public debate do not. In the book’s last chapter, Born and Barry focus on how new publics can be created in the intersection between science and art. In a comparative study between a U.K. and a U.S. case, they show how the cooperation between artist and scientist mostly has been thought of as art helping science to communicate its knowledge to the lay public. But they also show that these relations can be thought of in other ways and that art can play a vital role in developing sciences by raising questions, engaging publics, and producing different kinds of knowledge. This relation is, as Born and Barry show, not straightforward, and art/science initiatives and institutions are often met with resistance from well-established scientific and technical disciplines. Other chapters do not seem to follow the analytical tracks laid out by Born and Barry, but some of them are still recommended for understanding interdisciplinarity. The chapters by Osborne and Sheila Jasanoff are especially worth reading. Osborne offers one of the book’s more theoretical analyses, and he approaches a discussion that is curiously lacking in the literature on interdisciplinarity— namely, theoretical considerations about disciplines—in a highly interesting way. Disciplines are, Osborne argues, taken for granted in research policy calls for interdisciplinarity. This has large implications not only for research and research funding, but also for education, since it would imply that classical disciplinary education remains prioritized. Jasanoff’s chapter is a reflexive account of the genesis of STS. It shows how ‘‘disciplines’’ emerge and are institutionalized through struggles both internally and with established academic and societal interests. Interdisciplinarity shows that the call for accountability and science in society does not affect all scientific disciplines equally. The main message, even though it is not spelled out that clearly, seems to be that this call changes conditions dramatically for the ‘‘soft’’ and critical social sciences, since accountability and usefulness are predominantly translated to industrial, economic, and instrumental codes.

Process-Tracing Methods: Foundations and GuidelinesProcess-Tracing Methods: Foundations and Guidelines, by BeachDerekPedersenRasmus Brun. Ann Arbor: University of Michigan Press, 2013. 199 pp.

tal problems. Weszkalnys and Barry show how ambitions to create new interdisciplinary research institutions accountable to the public played out very differently in different settings. Not only did different national traditions provide different organizational possibilities, but these differences were incorporated differently into the organization and knowledge production of the institution. Academic publication becomes a hard measure for public accountability for all three institutions, but other kinds of outreach or contributions to the public debate do not. In the book’s last chapter, Born and Barry focus on how new publics can be created in the intersection between science and art. In a comparative study between a U.K. and a U.S. case, they show how the cooperation between artist and scientist mostly has been thought of as art helping science to communicate its knowledge to the lay public. But they also show that these relations can be thought of in other ways and that art can play a vital role in developing sciences by raising questions, engaging publics, and producing different kinds of knowledge. This relation is, as Born and Barry show, not straightforward, and art/science initiatives and institutions are often met with resistance from well-established scientific and technical disciplines. Other chapters do not seem to follow the analytical tracks laid out by Born and Barry, but some of them are still recommended for understanding interdisciplinarity. The chapters by Osborne and Sheila Jasanoff are especially worth reading. Osborne offers one of the book’s more theoretical analyses, and he approaches a discussion that is curiously lacking in the literature on interdisciplinarity— namely, theoretical considerations about disciplines—in a highly interesting way. Disciplines are, Osborne argues, taken for granted in research policy calls for interdisciplinarity. This has large implications not only for research and research funding, but also for education, since it would imply that classical disciplinary education remains prioritized. Jasanoff’s chapter is a reflexive account of the genesis of STS. It shows how ‘‘disciplines’’ emerge and are institutionalized through struggles both internally and with established academic and societal interests. Interdisciplinarity shows that the call for accountability and science in society does not affect all scientific disciplines equally. The main message, even though it is not spelled out that clearly, seems to be that this call changes conditions dramatically for the ‘‘soft’’ and critical social sciences, since accountability and usefulness are predominantly translated to industrial, economic, and instrumental codes.