The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

This 1989 book is intended as an introductory survey of the philosophy of the social sciences. It is essentially a work of exposition which offers a toolbox of mechanisms - nuts and bolts, cogs and wheels - that can be used to explain complex social phenomena. Within a brief compass, Jon Elster covers a vast range of topics. His point of departure is the conflict we all face between our desires and our opportunities. How can rational choice theory help us (...) understand our motivation and behaviour? More significantly, what happens when the theory breaks down but we still cleave to a belief in the power of the rational? Elster describes the fascinating range of forms of irrationality - wishful thinking, the phenomenon of sour grapes, discounting the future in noncooperative behaviour. This is a remarkably lucid and comprehensive introduction to the social sciences for students of political science, philosophy, sociology and economics. (shrink)

This text focuses on the theory of popular politics constructed within the context of analytical Marxism, and asks if rational choice theory provides an adequate basis for explaining patterns of social, political and economic behaviour in traditional China.

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)