Science has its beginning points and ending points in theoretical and practical philosophy. This little book gives a brief introduction to the philosophical issues involved in doing science by illustrating the issues under the classical divisions: Epistemology of Science, Scientific Metaphysics, and Ethics of Science. The book is for beginners.

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The transferability problem—whether the results of an experiment will transfer to a treatment population—affects not only Randomized Controlled Trials but any type of study. The problem for any given type of study can also, potentially, be addressed to some degree through many different types of study. The transferability problem for a given RCT can be investigated further through another RCT, but the variables to use in the further experiment must be discovered. This suggests we could do better on the epistemological (...) problem of transferability by promoting, in the repeated process of formulating public health guidelines, feedback loops of information from the implementation setting back to researchers who are defining new studies. (shrink)

So far no known measure of confirmation of a hypothesis by evidence has satisfied a minimal requirement concerning thresholds of acceptance. In contrast, Shogenji’s new measure of justification (Shogenji, Synthese, this number 2009) does the trick. As we show, it is ordinally equivalent to the most general measure which satisfies this requirement. We further demonstrate that this general measure resolves the problem of the irrelevant conjunction. Finally, we spell out some implications of the general measure for the Conjunction Effect; in (...) particular we give an example in which the effect occurs in a larger domain, according to Shogenji justification, than Carnap’s measure of confirmation would have led one to expect. (shrink)

Can some evidence confirm a conjunction of two hypotheses more than it confirms either of the hypotheses separately? We show that it can, moreover under conditions that are the same for nine different measures of confirmation. Further we demonstrate that it is even possible for the conjunction of two disconfirmed hypotheses to be confirmed by the same evidence.

In his discussion of the paradox of the ravens,1 Mark Sainsbury takes the paradox to show the falsity of the following principle: G1. A generalisation is confirmed by any of its instances. The other possibilities, he argues, are to accept the paradoxical conclusion, or to reject the other principle involved.

In sum, then, Chalmers’s attempt to argue against physicalism based on the conceivability of zombies misses the mark. His version of conceivability does indeed imply possibility, but at the cost of making it unclear whether zombies are indeed conceivable.

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premisses and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. This approach explains (...) why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that (...) none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures. (shrink)

It is commonly acknowledged that, in order to test a theoretical hypothesis, one must, in Duhem' s phrase, rely on a "theoretical scaffolding" to connect the hypothesis with something measurable. Hypothesis-confirmation, on this view, becomes a three-place relation: evidence E will confirm hypothesis H only relative to some such scaffolding B. Thus the two leading logical approaches to qualitative confirmation--the hypothetico-deductive (H-D) account and Clark Glymour' s bootstrap account--analyze confirmation in relative terms. But this raises questions about the philosophical interpretation (...) of the technical conditions these accounts describe. What does it mean to say that E confirms H "relative to B"? How should we interpret the relation we are trying to analyze? (shrink)

In this paper I examine Quine''s indispensability argument, with particular emphasis on what is meant by ''indispensable''. I show that confirmation theory plays a crucial role in answering this question and that once indispensability is understood in this light, Quine''s argument is seen to be a serious stumbling block for any scientific realist wishing to maintain an anti-realist position with regard to mathematical entities.

Bayesian epistemology postulates a probabilistic analysis of many sorts of ordinary and scientific reasoning. Huber ([2005]) has provided a novel criticism of Bayesianism, whose core argument involves a challenging issue: confirmation by uncertain evidence. In this paper, we argue that under a properly defined Bayesian account of confirmation by uncertain evidence, Huber's criticism fails. By contrast, our discussion will highlight what we take as some new and appealing features of Bayesian confirmation theory. Introduction Uncertain Evidence and Bayesian Confirmation Bayesian Confirmation (...) by Uncertain Evidence: Test Cases and Basic Principles CiteULike Connotea Del.icio.us What's this? (shrink)

The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of confirmation relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal (...) result is a confirmation-theoretic account of the conjunction fallacy, which is proven robust (i.e., not depending on various alternative ways of measuring degrees of confirmation). The proposed analysis is shown distinct from contentions that the conjunction effect is in fact not a fallacy, and is compared with major competing explanations of the phenomenon, including earlier references to a confirmation-theoretic account. (shrink)

In this paper, we identify a new and mathematically well-defined sense in which the coherence of a set of hypotheses can be truth-conducive. Our focus is not, as usually, on the probability but on the confirmation of a coherent set and its members. We show that, if evidence confirms a hypothesis, confirmation is "transmitted" to any hypotheses that are sufficiently coherent with the former hypothesis, according to some appropriate probabilistic coherence measure such as Olsson’s or Fitelson’s measure. Our findings have (...) implications for scientific methodology, as they provide a formal rationale for the method of indirect confirmation and the method of confirming theories by confirming their parts. (shrink)

Glymour’s theory of bootstrap confirmation is a purely qualitative account of confirmation; it allows us to say that the evidence confirms a given theory, but not that it confirms the theory to a certain degree. The present paper extends Glymour’s theory to a quantitative account and investigates the resulting theory in some detail. It also considers the question how bootstrap confirmation relates to justification.