The basic understanding which underlies scientific evidence - ideas such as the structure of experiments, causality, repeatability, validity and reliability- is not straightforward. But these ideas are needed to judge evidence in school science, in physics or chemistry or biology or psychology, in undergraduate science, and in understanding everyday issues to do with science. It is essential to be able to be critical of scientific evidence. The authors clearly set out the principles of investigation so that the reader will be (...) confident in questioning the experts, making an informed choice or arriving at in informed opinion. The book is intended for a wide range of readers including those who want to: } collect their own evidence } be able to question and judge a wide range of science-based issues that we come across in the press or other media in everyday life } teach others how to understand evidence. This book has been developed from the authors' work with first year undergraduates in a combined science course and in primary teacher training for science specialists. It is suitable for students training as primary science specialists, and also for 'A' level and first-year undergraduates in science and science-related subjects. (shrink)

The end of the nineteenth century and the whole of the twentieth may justifiably be called a time of great discoveries in the micro-, macro-, and megaworlds. All bearing witness to the dynamic life of the universe, these discoveries have resulted primarily from progress in the instruments of research, leading to the discovery of many new elementary particles, new forms of interaction, fields, and astrophysical objects — quasars, pulsars, sources of X-ray emissions, and others. An understanding of the essence of (...) the processes involved in these objects and phenomena, however, comes up against certain difficulties , the overcoming of which is to be sought primarily along the lines of further improvement of the tools of research and processing of the information acquired, the application of existing theories and the development of new ones in physics and astrophysics, and the utilization of the achievements of the science of the most general laws of the motion and development of nature, society, and thought, i.e., dialectical materialism, as the general methodology of acquisition of scientific knowledge. (shrink)

This paper argues for a comprehensive conception of empathy as comprising epistemic, affective, and motivational elements and introduces the ancient Stoic theory of attachment as a model for describing the embodied, emotional response to others that we take to be distinctive of empathy. Our argument entails that in order to provide a suitable conceptual framework for the interdisciplinary study of empathy one must extend the scope of recent “simulationalist” and “enactivist” accounts of empathy in two important respects. First, against the (...) enactivist assumption that human mindreading capacities primarily rely on an immediate, quasi-perceptual understanding of other’s intentional states, we draw on Alfred Schutz’ analysis of social understanding to argue that reflective types of understanding play a distinct, but equally fundamental role in empathic engagements. Second, we insist that empathy also involves an affective response toward the other and their situation. We suggest analyzing this response in terms of the Stoic concepts of attachment, concern, and a fundamental type of prosocial motivation, that can best be described as an “extended partiality.” By way of conclusion, we integrate the above concepts into a comprehensive conceptual framework for the study of empathy and briefly relate them to current debates about empathic perception and prosocial motivation. The result, we argue, is an account that stays neutral with regard to the exact nature of the processes involved in producing empathy and can therefore accommodate discussion across theoretical divides—e.g., those between enactivist, simulationalist, and so-called theory-theorist approaches. (shrink)

Prism adaptation is a form of visuomotor training that produces both sensorimotor and cognitive aftereffects depending on the direction of the visual displacement. Recently, a neural framework explaining both types of PA-induced aftereffects has been proposed, but direct evidence for it is lacking. We employed Structural Equation Modeling, a form of effective connectivity analysis, to establish directionality among connected nodes of the brain network thought to subserve PA. The findings reveal two distinct network branches: a loop involving connections from the (...) parietal cortices to the right parahippocampal gyrus, and a branch linking the lateral premotor cortex to the parahippocampal gyrus via the cerebellum. Like the sensorimotor aftereffects, the first branch exhibited qualitatively different modulations for left versus right PA, and critically, changes in these connections were correlated with the magnitude of the sensorimotor aftereffects. Like the cognitive aftereffects, changes in the second branch were qualitatively similar for left and right PA, with greater change for left PA and a trend correlation with cognitive aftereffects. These results provide direct evidence that PA is supported by two functionally distinct subnetworks, a parietal–temporal network responsible for sensorimotor aftereffects and a fronto-cerebellar network responsible for cognitive aftereffects. (shrink)

We share with Anderson & Lebiere (A&L) (and with Newell before them) the goal of developing a domain-general framework for modeling cognition, and we take seriously the issue of evaluation criteria. We advocate a more focused approach than the one reflected in Newell's criteria, based on analysis of failures as well as successes of models brought into close contact with experimental data. A&L attribute the shortcomings of our parallel-distributed processing framework to a failure to acknowledge a symbolic level of thought. (...) Our framework does acknowledge a symbolic level, contrary to their claim. What we deny is that the symbolic level is the level at which the principles of cognitive processing should be formulated. Models cast at a symbolic level are sometimes useful as high-level approximations of the underlying mechanisms of thought. The adequacy of this approximation will continue to increase as symbolic modelers continue to incorporate principles of parallel distributed processing. (shrink)