A quantitative analysis of the relationship between the Cook-Medley Hostility Scale and traditional coronary artery disease risk factors.

One possible explanation for the association between Cook-Medley Hostility Scale (Ho Scale; W. W. Cook & D. M. Medley, 1954) scores and premature coronary artery disease (CAD) morbidity and mortality is that hostile persons also have elevations on CAD risk factors. Meta-analyses with fixed and random-effects models were used to evaluate the relationship between Ho Scale scores and CAD risk factors in the empirical literature. Ho Scale scores were significantly related to body mass index, waist-to-hip ratio, insulin resistance, lipid ratio, triglycerides, glucose, socioeconomic status (SES), alcohol consumption, and smoking. Although there was also heterogeneity among study outcomes, the results of conservative random effects models provide confidence in the obtained relationships. On the basis of available evidence, researchers might give attention to obesity, insulin resistance, damaging health behaviors, and SES as potential contributing factors in understanding the association between Ho Scale scores and CAD.     

Feyerabend’s well-ordered science: how an anarchist distributes funds

To anyone vaguely aware of Feyerabend, the title of this paper would appear as an oxymoron. For Feyerabend, it is often thought, science is an anarchic practice with no discernible structure. Against this trend, I elaborate the groundwork that Feyerabend has provided for the beginnings of an approach to organizing scientific research. Specifically, I argue that Feyerabend’s pluralism, once suitably modified, provides a plausible account of how to organize science. These modifications come from C.S. Peirce’s account of the economics of theory pursuit, which has since been corroborated by empirical findings in the social sciences. I go on to contrast this approach with the conception of a ‘well-ordered science’ as outlined by Kitcher (Science, truth, and democracy, Oxford University Press, New York, 2001), Cartwright (Philos Sci 73(5):981–990, 2006), which rests on the assumption that we can predict the content of future research. I show how Feyerabend has already given us reasons to think that this model is much more limited than it is usually understood. I conclude by showing how models of resource allocation, specifically those of Kitcher (J Philos 87:5–22, 1990), Strevens (J Philos 100(2):55–79, 2003) and Weisberg and Muldoon (Philos Sci 76(2):225–252, 2009), unwittingly make use of this problematic assumption. I conclude by outlining a proposed model of resource allocation where funding is determined by lottery and briefly examining the extent to which it is compatible with the position defended in this paper.

     

Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.