Julian Reiss

This volume reflects the ‘philosophy of science in practice’ approach and takes a fresh look at traditional philosophical problems in the context of natural, social, and health research. Inspired by the work of Nancy Cartwright that shows how the practices and apparatuses of science help us to understand science and to build theories in the philosophy of science, this volume critically examines the philosophical concepts of evidence, laws, causation, and models and their roles in the process of scientific reasoning. Each chapter is an important one in the philosophy of science, while the volume as a whole deals with these philosophical concepts in a unified way in the context of actual scientific practice. This volume thus aims to contribute to this new direction in the philosophy of science.​

The most fundamental questions of economics are often philosophical in nature, and philosophers have, since the very beginning of Western philosophy, asked many questions that current observers would identify as economic. The Routledge Handbook of Philosophy of Economics is an outstanding reference source to the key topics, problems, and debates at the intersection of philosophical and economic inquiry.It captures this field of countless exciting interconnections, affinities, and opportunities for cross-fertilization. Comprising thirty-five chapters by a diverse team of contributors from all over the globe, the Handbook is divided into eight sections: I. Rationality II. Cooperation and Interaction III. Methodology IV. Values V. Causality and Explanation VI. Experimentation and Simulation VII. Evidence VIII. Policy The volume is essential reading for students and researchers in economics and philosophy who are interested in exploring the interconnections between the two disciplines. It is also a valuable resource for those in related fields like political science, sociology, and in the humanities.

Jeffrey Friedman’s Power Without Knowledge argues forcefully that there are inherent limitations to the predictability of human action, due to a circumstance he calls “ideational heterogeneity.” However, our resources for predicting human action somewhat reliably in the light of ideational heterogeneity have not been exhausted yet, and there are no in-principle barriers to progress in tackling the problem. There are, however, other strong reasons to think that disagreement among epistocrats is bound to persist, such that it will be difficult to decide who has “the right answer” to a given technocratic problem. These reasons have to do with competing visions of the good society, fact/value entanglement, and the fragility of the facts of the social sciences.

Acceding to the demand that public policy should be based on “the best available evidence” can come at significant moral cost. Important policy questions cannot be addressed using “the best available evidence” as defined by the evidence-based policy paradigm; the paradigm can change the meaning of questions so that they can be addressed using the preferred kind of evidence; and important evidence that does not meet the standard defined by the paradigm can get ignored. We illustrate these problems in three contexts of evidence-based policy.

This encyclopedia is the first of its kind in bringing together philosophy and the social sciences. It is not only about the philosophy of the social sciences but, going beyond that, it is also about the relationship between philosophy and the social sciences. The subject of this encyclopedia is purposefully multi- and inter-disciplinary. Knowledge boundaries are both delineated and crossed over. The goal is to convey a clear sense of how philosophy looks at the social sciences and to mark out a detailed picture of how the two are interrelated: interwoven at certain times but also differentiated and contrasted at others. The Entries cover topics of central significance but also those that are both controversial and on the cutting-edge, underlining the unique mark of this Encyclopedia: the interrelationship between philosophy and the social sciences, especially as it is found in fresh ideas and unprecedented hybrid disciplinary areas. The Encyclopedia serves a further dual purpose: it contributes to the renewal of the philosophy of the social sciences and helps to promote novel modes of thinking about some of its classic problems.

In the human sciences, experimental research is used to establish causal relationships. However, the extrapolation of these results to the target population can be problematic. To facilitate extrapolation, we propose to use the statistical technique Latent Class Regression Analysis in combination with the analogical reasoning theory for extrapolation. This statistical technique can identify latent classes that differ in the effect of X on Y. In order to extrapolate by means of analogical reasoning, one can characterize the latent classes by a combination of features, and then compare these features to features of the target.

Francesco Guala once wrote that ‘The problem of extrapolation is a minor scandal in the philosophy of science’. This paper agrees with the statement, but for reasons different from Guala’s. The scandal is not, or not any longer, that the problem has been ignored in the philosophy of science. The scandal is that framing the problem as one of external validity encourages poor evidential reasoning. The aim of this paper is to propose an alternative—an alternative which constitutes much better evidential reasoning about target systems of interest, and which makes do without consideration of external validity.

This paper reviews all major theories of evidence such as the Bayesian theory, hypothetico-deductivism, satisfaction theories, error-statistics, Achinstein's explanationist theory and Cartwright's argument theory. All these theories fail to take adequate account of the context in which a hypothesis is established and used. It is argued that the context of an inquiry determines important facts about what evidence is, and how much and what kind has to be collected to establish a hypothesis for a given purpose.

This volume reflects the ‘philosophy of science in practice’ approach and takes a fresh look at traditional philosophical problems in the context of natural, social, and health research. Inspired by the work of Nancy Cartwright that shows how the practices and apparatuses of science help us to understand science and to build theories in the philosophy of science, this volume critically examines the philosophical concepts of evidence, laws, causation, and models and their roles in the process of scientific reasoning. Each chapter is an important one in the philosophy of science, while the volume as a whole deals with these philosophical concepts in a unified way in the context of actual scientific practice. This volume thus aims to contribute to this new direction in the philosophy of science.​

Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science, but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of models and theories, and the relation between experimentation and theorising, and submit that simulations demand a fundamentally new philosophy of science in many respects. The aim of this paper is to critically evaluate these claims. Our conclusion will be sober. We argue that these claims are overblown and that simulations, far from demanding a new metaphysics, epistemology, semantics and methodology, raise few if any new philosophical problems. The philosophical problems that do come up in connection with simulations are not specific to simulations and most of them are variants of problems that have been discussed in other contexts before.

This paper looks at an appeal to the authority of biomedical research that has recently been used by empirical economists to motivate and justify their methods. I argue that those who make this appeal mistake the nature of biomedical research. Randomised trials, which are said to have revolutionised biomedical research, are a central methodology, but according to only one paradigm. There is another paradigm at work in biomedical research, the inferentialist paradigm, in which randomised trials play no special role. I outline the inferentialist alternative in broad strokes, apply it to a recent controversy in econometrics and draw some general conclusions concerning econometric methodology