In the mid-eighteenth century David Hume argued that successful prediction tells us nothing about the truth of the predicting theory. But physical theory routinely predicts the values of observable magnitudes within very small ranges of error. The chance of this sort of predictive success without a true theory suggests that Hume's argument is flawed. However, Colin Howson argues that there is no flaw and examines the implications of this disturbing conclusion; he also offers a solution to one of the central (...) problems of Western philosophy, the problem of induction. (shrink)

In this book, Roy Bhaskar sets out to revindicate ontology, critiquing the reduction of being in favor of knowledge, which he calls the "epistemic fallacy".

The generality problem is widely considered to be a devastating objection to reliabilist theories of justification. My goal in this paper is to argue that a version of the generality problem applies to all plausible theories of justification. Assume that any plausible theory must allow for the possibility of reflective justification—S's belief, B, is justified on the basis of S's knowledge that she arrived at B as a result of a highly (but not perfectly) reliable way of reasoning, R. The (...) generality problem applies to all cases of reflective justification: Given that is the product of a process-token that is an instance of indefinitely many belief-forming process-types (or BFPTs), why is the reliability of R, rather than the reliability of one of the indefinitely many other BFPTs, relevant to B's justificatory status? This form of the generality problem is restricted because it applies only to cases of reflective justification. But unless it is solved, the generality problem haunts all plausible theories of justification, not just reliabilist ones. (shrink)

The contemporary explosion of information makes intellectual responsibility more needed than ever. The uncritical tend to believe too much that is unsubstantiated; the overcritical tend to believe too little that is true. A central problem for this paper is to formulate standards to guide an intellectually rigorous search for a mean between excessive credulity and indiscriminate skepticism. A related problem is to distinguish intellectual responsibility for what we believe from moral responsibility for what we do. A third problem is how (...) to square intellectual responsibility in retaining our views with the realization that peers we respect disagree with us. Much of the paper is directed to articulating principles for dealing with such disagreements. (shrink)

In this paper the use value of qualitative research findings to nurses in practice is questioned. More precisely it is argued that, insofar as action follows belief then, in all but the rarest of cases, the beliefs that nurses in practice can justifiably derive from or form on the basis of qualitative research findings do not sanction action in the world and the assumption, apparently widely held, that qualitative research can as evidence productively inform practice collapses. If qualitative research does (...) not have a substantive action guiding potential then, in consequence, three conclusions are permitted. First, regarding the requirement that nurses ground actions on evidence, regulators should redraft methodologically neutral or permissive guidelines to specify the sorts of research evidence that can serve this function. Second, qualitative methodologies should receive less prominence in nurse education programmes. Third, qualitative researchers should make it clear that their work cannot inform practice. Alternatively, if this claim is advanced the process by which this is to be achieved should be explicitly stated. (shrink)

Turning his back on neoliberalism, voicing 'the end of history' and the unstoppable spread of liberal values across the globe, Gray's was a lone voice of scepticism. The thinking he criticised would lead to the invasion of Iraq. Today, its folly might seem obvious, but Gray has been trying to warn us for years.

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics (...) as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)