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An international team of four authors, led by distinguished philosopher of science, Nancy Cartwright, and leading scholar of the Vienna Circle, Thomas E. Uebel, have produced this lucid and elegant study of a much-neglected figure. The book, which depicts Neurath's science in the political, economic and intellectual milieu in which it was practised, is divided into three sections: Neurath's biographical background and the socio-political context of his economic ideas; the development of his theory of science; and his legacy as illustrated by his contemporaneous involvement in academic and political debates. Coinciding with the renewal of interest in logical positivism, this is a timely publication which will redress a current imbalance in the history and philosophy of science, as well as making a major contribution to our understanding of the intellectual life of Austro-Germany in the inter-war years

AbstractThis paper defends the need for evidential diversity and the mix of methods that that can in train require. The focus is on causal claims, especially 'singular' claims about the effects of causes in a specific setting—either what will happen or what has happened. I do so by offering a template that categorises kinds of evidence that can support these claims. The catalogue is generated by considering what needs to happen for a causal process to carry through from putative cause at the start to the targeted effect at the end. The usual call for mixed methods focusses on a single overall claim and argues that we increase certainty by the use of different methods with compensating strengths and weaknesses. My proposals instead focus on the evidence that supports the great many subsidiary claims that must hold if the overall one is to be true. As is typical for singular causal claims, the mix of methods that will generally be required to collect the kinds of evidence I urge will usually have little claim to the kind of rigour that is now widely demanded in evidencing causal claims, especially those for policy/treatment effectiveness. So I begin with an exploration of what seems to be intended by 'rigour' in such discussions, since it is seldom made clear just what makes the favoured methods especially rigorous. I then argue that the emphasis on rigour can be counterproductive. Rigour is often the enemy of evidential diversity, and evidential diversity—lots of it—can make for big improvements in the reliability of singular causal predictions and post hoc evaluations. I illustrate with the paragon of rigour for causal claims, randomised controlled trials (RCTs), rehearsing at some length what they can and cannot do to make it easier to assess the importance of rigour in warranting singular causal claims.

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: structural 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 than 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.

When is a well-established study result that a given policy/programme/treatment produced a given outcome in a particular study setting ('there') evidence that that policy/programme/ treatment will produce that outcome in a new setting ('here')? This paper insists that 'there' and 'here' be firmly distinguished and offers in answer that we must have evidence that two further facts obtain: (a) that the policy can play the same causal role widely (widely enough to cover both here and there) and (b) that a complete set of the support factors necessary for the policy to operate here are present in some individuals here.

This is a much-needed new introduction to a field that has been transformed in recent years by exciting new subjects, ideas, and methods. It is designed both for students with central interests in philosophy and those planning to concentrate on the social sciences, and it presupposes no particular background in either domain. From the wide range of topics at the forefront of debate in philosophy of social science, the editors have chosen those which are representative of the most important and interesting contemporary work. A team of distinguished experts explore key aspects of the field such as social ontology (what are the things that social science studies?), objectivity, formal methods, measurement, and causal inference. Also included are chapters focused on notable subjects of social science research, such as well-being and climate change. Philosophy of Social Science provides a clear, accessible, and up-to-date guide to this fascinating field. -- Back cover

Over the last twenty or so years, it has become standard to require policymakers to base their recommendations on evidence. That is now uncontroversial to the point of triviality - of course, policy should be based on the facts. But are the methods that policy makers rely on to gather and analyse evidence the right ones? This book explains that the dominant methods which are in use now - broadly speaking, methods that imitate standard practices in medicine, like randomised control trials - do not work. They fail because they do not enhance our ability to predict if policies will be effective