This collects some of the remarks made at the 2016 Pacific APA Memorial session for Patrick Suppes and Jaakko Hintikka. The full list of speakers on behalf of these two philosophers: Dagfinn Follesdal; Dana Scott; Nancy Cartwright; Paul Humphreys; Juliet Floyd; Gabriel Sandu; John Symons.

Hunting Causes and Using Them argues that causation is not one thing, as commonly assumed, but many. There is a huge variety of causal relations, each with different characterizing features, different methods for discovery and different uses to which it can be put. In this collection of new and previously published essays, Nancy Cartwright provides a critical survey of philosophical and economic literature on causality, with a special focus on the currently fashionable Bayes-nets and invariance methods - and (...) it exposes a huge gap in that literature. Almost every account treats either exclusively how to hunt causes or how to use them. But where is the bridge between? It's no good knowing how to warrant a causal claim if we don't know what we can do with that claim once we have it. This book will interest philosophers, economists and social scientists. (shrink)

(No abstract is available for this citation).

It is often supposed that the spectacular successes of our modern mathematical sciences support a lofty vision of a world completely ordered by one single elegant theory. In this book Nancy Cartwright argues to the contrary. When we draw our image of the world from the way modern science works - as empiricism teaches us we should - we end up with a world where some features are precisely ordered, others are given to rough regularity and still others (...) behave in their own diverse ways. This patchwork makes sense when we realise that laws are very special productions of nature, requiring very special arrangements for their generation. Combining classic and newly written essays on physics and economics, The Dappled World carries important philosophical consequences and offers serious lessons for both the natural and the social sciences. (shrink)

In this sequence of philosophical essays about natural science, the author argues that fundamental explanatory laws, the deepest and most admired successes of modern physics, do not in fact describe regularities that exist in nature. Cartwright draws from many real-life examples to propound a novel distinction: that theoretical entities, and the complex and localized laws that describe them, can be interpreted realistically, but the simple unifying laws of basic theory cannot.

Nancy Cartwright; XII*—Fundamentalism vs. the Patchwork of Laws, Proceedings of the Aristotelian Society, Volume 94, Issue 1, 1 June 1994, Pages 279–292, https.

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities (...) to the explanation of the role of causality in quantum mechanics. (shrink)

La autora presenta algunas criticas generales al proyecto de reducir las leyes causales a probabilidades. Además, muestra que las leyes causales son imprescindibles para poder diferenciar las strategias efectivas de las que no lo son y da un criterio para considerar cuando podemos deducir causalidad a través de datos estadísticos.

We currently have on offer a variety of different theories of causation. Many are strikingly good, providing detailed and plausible treatments of exemplary cases; and all suffer from clear counterexamples. I argue that, contra Hume and Kant, this is because causation is not a single, monolithic concept. There are different kinds of causal relations imbedded in different kinds of systems, readily described using thick causal concepts. Our causal theories pick out important and useful structures that fit some familiar cases—cases we (...) discover and ones we devise to fit. (shrink)

How fixed are the happenings in Nature and how are they fixed? One - very orthodox - account teaches that the sciences offer general truths that we combine with local facts to derive our expectations about what will happen, either naturally or when we build a device to design, be it a laser, a washing machine, an anti-malarial bed net, or an auction for the airwavse. Nancy Cartwright offers a different picture, one in which neither we nor Nature (...) have such nice rules to go by. This volume includes her Paul Carus Lectures plus four additional papers that further develop some of the central ideas. Cartwright offers an original view on the age-old question of scientific realism in which our knowledge is genuine, yet our scientific principles are neither true nor false but are, rather, templates for building good models. (shrink)

Mechanisms are now taken widely in philosophy of science to provide one of modern science’s basic explanatory devices. This has raised lively debate concerning the relationship between mechanisms, laws and explanation. This paper focuses on cases where a mechanism gives rise to a ceteris paribus law, addressing two inter-related questions: What kind of explanation is involved? and What is going on in the world when mechanism M affords behavior B described in a ceteris paribus law? We explore various answers offered (...) by ‘new mechanists’ and others before setting out and explaining our own answers: mechanistic explanations are a species of oldfashioned covering-law explanation and this often accounts in part for their explanatory power; and B is what it takes for some set of principles that govern the features of M’s parts in their arrangement in M all to be instanced together. (shrink)

For evidence-based practice and policy, randomised controlled trials (RCTs) are the current gold standard. But exactly why? We know that RCTs do not, without a series of strong assumptions, warrant predictions about what happens in practice. But just what are these assumptions? I maintain that, from a philosophical stance, answers to both questions are obscured because we don't attend to what causal claims say. Causal claims entering evidence-based medicine at different points say different things and, I would suggest, failure to (...) attend to these differences makes much current guidance about evidence for medical and social policy misleading. (shrink)

Are the laws of nature consistent with contingency about what happens in the world? That depends on what the laws of nature actually are, but it also depends on what they are like. The latter is the concern of this chapter, which looks at three views that are widely endorsed: ‘Humean’ regularity accounts, laws as relations among universals, and disposition/powers accounts. Given an account of what laws are, what follows about how much contingency, and of what kinds, laws allow? In (...) all three cases, the authors argue, the root idea of what laws are does not settle the issue of whether they allow contingency. Advocates of the different accounts may argue for one view or another on the issue, but this will be an add-on rather than a consequence of the basic view about what laws are. -/- . (shrink)

Philosophers of science have had little to say about ‘middle-range theory’ although much of what is done in science and of what drives its successes falls under that label. These lectures aim to spark an interest in the topic and to lay groundwork for further research on it. ‘Middle’ in ‘middle range’ is with respect to the level both of abstraction and generality. Much middle-range theory is about things that come under the label ‘mechanism’. The lectures explore three different kinds (...) of mechanism: struc tural mechanisms or underlying systems that afford causal pathways; causal-chain mechanisms that are represented in what in policy contexts are called ‘theories of change’ and for which I give an extended account following the causal process theory of Wesley Salmon; and middle-range-law mechanisms like those discussed by Jon Elster, which I claim are —and rightly are— rampant throughout the social sciences. The theory of the democratic peace, that democracies do not go to war with democracies, serves as a running example. The discussions build up to the start of, first, an argument that reliability in social (and natural) science depends not so much on evidence as it does on the support of a virtuous tangle of practices (without which there couldn’t even be evidence), and second, a defence of a community-practice centred instrumentalist understanding of many of the central basic principles that we use (often successfully) in social (and in natural) science for explanation, prediction and evaluation. (shrink)

A good many models used in physics and economics offer descriptions of imaginary situations, using a combination of mathematics and natural language. The descriptions are both thin - not much about the situation is filled in - and unrealistic - what is filled in is not true of many real situations. Yet we want to use the results of these models to inform our conclusions about a range of actually occurring situations. I propose we interpret many of these models as (...) fables. The actual happenings in the model are only one concrete instantiation of a lesson that is more widely applicable ‘when expressed in more abstract language.' A fable generally comes with the abstract lesson attached; parables, by contrast, usually require an interpretation from outside. Models, then, tend to be more like parables than fables. The right abstract interpretation is not supplied by the model itself. The central problem, then, is where shall it come from? (shrink)

Four distinguished authors have been brought together to produce this elegant study of a much-neglected figure. The book is divided into three sections: Neurath's biographical background and the economic and social context of his ideas; his theory of science; and the development of his role in debates on Marxist concepts of history and his own conception of science. Coinciding with the emerging serious interest in logical positivism, this timely publication will redress a current imbalance in the history and philosophy of (...) science. (shrink)

The standard view of explanation in science---the covering law model---assumes that knowledge of laws lies at the basis of our ability to explain phenomena. But in fact most of the high-level claims in science are ceteris paribus generalizations, which are false unless certain precise conditions obtain. Given the explanatory force of ceteris paribus generalizations but the paucity of true laws, the covering law model of explanation must be false. There is, it is argued, a trade-off between truth and explanatory power.

In evaluating science, philosophers tends to focus on general laws and on their truth. I urge a shift in focus to the reliability of the panoply of outputs science produces and in tandem, from the general to the particular. Here I give five arguments to support this, including many, many scientific outputs, which must be supposed reliable if we are to warrant our general principles, aren’t truth-apt; and reliability invites the crucial question, ‘Reliable for what?’ Getting clear the particular purpose (...) is essential for effective action and just evaluation. (shrink)

This book presents a radical new picture of natural order. The Newtonian idea of a cosmos ruled by universal and exceptionless laws has been superseded; replaced by a conception of nature as a realm of diverse powers, potencies, and dispositions, a 'dappled world'. There is order in nature, but it is more local, diverse, piecemeal, open, and emergent than Newton imagined. In each chapter expert authors expound the historical context of the idea of laws of nature, and explore the diverse (...) sorts of order actually presupposed by work in physics, biology, and the social sciences. They consider how human freedom might be understood, and explore how Newton's idea of a 'universal designer' might be revised, in this new context. They argue that there is not one unified totalizing program of science, aiming at the completion of one closed causal system. We live in an ordered universe, but we need to rethink the classical idea of the 'laws of nature' in a more dynamic and creatively diverse way. (shrink)

It is common, following Quine, to look to what theories say to determine the ontological commitments of a scientific discipline. But methods and practices are equally telling. This paper considers early doctrines in econometrics. It argues that what is directly confirmed in tests of the theory will not support the applications to which the theory is to be put unless we can assume a kind of stability and atomism characteristic of capacities. The leap from confirmation to application will only be (...) valid in a world where capacities are at work. (shrink)

There is a takeover movement fast gaining influence in development economics, a movement that demands that predictions about development outcomes be based on randomized controlled trials. The problem it takes up—of using evidence of efficacy from good studies to predict whether a policy will be effective if we implement it—is a general one, and affects us all. My discussion is the result of a long struggle to develop the right concepts to deal with the problem of warranting effectiveness predictions. Whether (...) I have it right or not, these are questions of vast social importance that philosophers of science can, and should, help answer. (shrink)

This book on the philosophy of science argues for an empiricism, opposed to the tradition of David Hume, in which singular rather than general causal claims are primary; causal laws express facts about singular causes whereas the general causal claims of science are ascriptions of capacities or causal powers, capacities to make things happen. Taking science as measurement, Cartwright argues that capacities are necessary for science and that these can be measured, provided suitable conditions are met. There are case (...) studies from both econometrics and quantum mechanics. (shrink)

Science is remarkably reliable. It puts people on the moon, performs laser eye surgery, tells us about ancient civilisations and species, and predicts the future of our climate. What underwrites this reliability? This book argues that the standard answers—the scientific method, rigour, and objectivity—are insufficient for the job. Here we propose a new model of science that places its products front and centre. This is the ‘Tangle of Science’. In this book we show how any reliable piece of science is (...) underpinned by a vast, diverse, and thick network of other scientific products. In doing so we bring back into focus areas of science that have been long neglected, emphasising how every product, from the screws that hold the space shuttle together to ways of measuring the consumer price index to Einstein’s theory of general relativity, work together to support results we can trust. (shrink)

What is science and what can it do? Nancy Cartwright here takes issue with three common images of science: that it amounts to the combination of theory and experiment; that all science is basically reducible to physics; and that science and the natural world which it pictures are deterministic. The author's innovative and thoughtful book draws on examples from the physical, life, and social sciences alike, and focuses on all the products of science – not just experiments or (...) theories – and how they work together. She reveals just what it is that makes science ultimately reliable, and how this reliability is nevertheless still compatible with a view of nature as more responsive to human change than we might think. Her book is a call for greater intellectual humility by and within scientific institutions. It will have strong appeal to anyone who thinks about science and how it is practised in society. (shrink)

We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction of one of (...) the first comprehensive model of superconductivity by London brothers in 1934. Instead of theory-driven view of models, we suggest a phenomenologically-driven one. (shrink)

Opponents of ceteris paribus laws are apt to complain that the laws are vague and untestable. Indeed, claims to this effect are made by Earman, Roberts and Smith in this volume. I argue that these kinds of claims rely on too narrow a view about what kinds of concepts we can and do regularly use in successful sciences and on too optimistic a view about the extent of application of even our most successful non-ceteris paribus laws. When it comes to (...) testing, we test ceteris paribus laws in exactly the same way that we test laws without the ceteris paribus antecedent. But at least when the ceteris paribus antecedent is there we have an explicit acknowledgment of important procedures we must take in the design of the experiments — i.e., procedures to control for “all interferences” even those we cannot identify under the concepts of any known theory. (shrink)

In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward ([1999]) put forward two independent theses, which they label ‘level invariance’ and ‘manipulability’, and they claim that, given a specific set of assumptions, manipulability implies the causal Markov condition. These claims are interesting and important, and this paper is devoted to commenting on them. With respect to level invariance, I argue that Hausman and Woodward's discussion is confusing because, as I point out, (...) they use different senses of ‘intervention’ and ‘invariance’ without saying so. I shall remark on these various uses and point out that the thesis is true in at least two versions. The second thesis, however, is not true. I argue that in their formulation, the manipulability thesis is patently false and that a modified version does not fare better. Furthermore, I think their proof that manipulability implies the causal Markov condition is not conclusive. In the deterministic case it is valid but vacuous, whereas it is invalid in the probabilistic case. 1 Introduction 2 Intervention, invariance and modularity 3 The causal Markov condition: CM1 and CM2 4 From MOD to the causal Markov condition and back 5 A second argument for CM2 6 The proof of the causal Markov condition for probabilistic causes 7 ‘Cartwright's objection’ defended 8 Metaphysical defenses of the causal Markov condition 9 Conclusion. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)