University of Edinburgh

Medicine is so pervasive in the modern Western world it seems difficult sometimes to understand what it is. This course explores the complex ways medicine is shaped by, and in turn, shapes us and the world we live in; whether medicine can be conceived as a system of knowledge, a form of power or an example of professional practice. The course focuses on some of the core theoretical insights that have emerged from the sociological studies of medicine, health, disease, and illness and is divided into two sections. In the first part, students look at the nature of medical professions, the relationships between clinicians and patients, biomedical power and knowledge, the rise of information communication and technology, empowered patient subjectivity and patient activism. In the second half of the course, students discuss the rise and status of public health (including some reflections on the social consequences of the coronavirus) and key contemporary issues in biomedicine (such as geneticization, pharmaceuticalization and cyborgization). We discuss the social and ethical consequences of these new medical (bio)technologies that may go 'beyond therapy' to enhancement. The question that runs throughout the course is whether, there is occurring a wider transformation from medicalization to biomedicalization that has changed what medicine was.

The course examines magical belief and supernatural entities in Scotland. This complex and much-neglected aspect of our cultural heritage is explored through a combination of empirical data (provided by case studies and archive holdings) and theoretical contextualization. A dominant theme is the identification and interpretation of vestiges of supernatural belief still extant and deeply embedded in Scottish cultural life. Comparative material from other Celtic-language cultures and Scandinavia also feature.

This is an advanced probability course dealing with discrete and continuous time Markov chains. The course covers the fundamental theory, and provides many examples. Markov chains has countless applications in many fields raging from finance, operation research and optimization to biology, chemistry, and physics.