Larry Laudan has challenged the realist to come up with a program that submits realism to "those stringent empirical demands which the realist himself minimally insists on when appraising scientific theories." This paper shows how the realist can go about taking up Laudan on this challenge; and, in such a way that the realist hypothesis actually ends up being confirmed, by any empirical standards. In other words, it is shown that we can test for convergent realism, just as readily as (...) Laudan can test for a connection between theories that are controlled by the cannons of science and their subsequent reliability. (shrink)

In “A Confutation of Convergent Realism,” Larry Laudan presents the realist with these fascinating challenges:What,then,of realism itself as a ‘scientific’ hypothesis?…If realism has made some novel predictions or been subjected to carefully controlled tests, one does not learn about it from the literature of contemporary realism. (1981, p. 46.)He then goes on to say:No proponent of realism has sought to show that realism satisfies those stringent empirical demands which the realist himself minimally insists on when appraising scientific theories. (1981, p. (...) 46)Not only do I fully endorse what Laudan says in these passages, I think it is time to take him up on these challenges.Laudan’s position has been that scientific progress can be explained without having to appeal to verisimilitude. Instead, we explain the success of a scientific theory in terms of its subjugation to the cannons of experimental controls: those theories that have been put through proper testing during the course of their formulation are the ones that are most likely to be reliable. (1984, pp. 96-101). (shrink)

This manual presents a carefully researched, detailed psychodynamic treatment program for the alleviation of a transdiagnostic range of primary Axis I anxiety disorders, including panic disorder, generalized anxiety disorder, social anxiety disorder, post-traumatic stress disorder, and related psychological problems. First exploring the principles of psychodynamic theory and formulation, the authors then present a three-phased process of Panic Focused Psychodynamic Psychotherapy-Extended Range : initial evaluation, interpretation of central conflicts and defense mechanisms, and termination. Each phase is discussed in depth and relies (...) on central case illustrations to demonstrate techniques and results. A subsequent chapter explores how to address complex issues that may arise during the course of treatment. Altogether, this manual not only provides a demonstrated, adaptable approach for anxiety disorders, but also clearly embodies a spirit of research and empiricism heretofore rare in psychodynamic psychotherapies, with an eye toward future development. (shrink)

In this paper, I analyze George Gaylord Simpson's response to the molecularization of evolutionary biology from his unique perspective as a paleontologist. I do so by exploring his views on early attempts to reconstruct phylogenetic relationships among primates using molecular data. Particular attention is paid to Simpson's role in the evolutionary synthesis of the 1930s and 1940s, as well as his concerns about the rise of molecular biology as a powerful discipline and world-view in the 1960s. I argue that Simpson's (...) belief in the supremacy of natural selection as the primary driving force of evolution, as well as his view that biology was a historical science that seeks ultimate causes and highlights contingency, prevented him from acknowledging that the study of molecular evolution was an inherently valuable part of the life sciences. (shrink)

Proponents of evidence-based medicine and some philosophers of science seem to agree that knowledge of mechanisms can help solve the problem of applying results of controlled studies to target populations (‘the problem of extrapolation’). We describe the problem of extrapolation, characterize mechanisms, and outline how mechanistic knowledge might be used to solve the problem. Our main thesis is that there are four often overlooked problems with using mechanistic knowledge to solve the problem of extrapolation. First, our understanding of mechanisms is (...) often (and arguably, likely to remain) incomplete. Secondly, knowledge of mechanisms is not always applicable outside the tightly controlled laboratory conditions in which it is gained. Thirdly, mechanisms can behave paradoxically. Fourthly, as Daniel Steel points out, using mechanistic knowledge faces the problem of the ‘extrapolator’s circle’. At the same time, when the problems with mechanistic knowledge have been addressed, such knowledge can and should be used to mitigate (nothing can entirely solve) the problem of extrapolation. (shrink)