Описание: Contents 1. A A country boy 2. A Pins and string 3. A Philosophy 4. A Learning to juggle 5. A Blue and yellow make pink 6. A Saturn and statistics 7. A Cast of characters 8. A Spinning cells 9. A The beautiful equations 10. A The Laird at home 11. A The Cavendish 12. A Last days 13. A Maxwella s legacy 14.
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.
A broad theory of research methodology for psychology and the behavioral sciences that offers a coherent treatment of a range of behavioral research methods.
This book considers scientific method in the behavioral sciences, with particular reference to psychology. Psychologists learn about research methods and use them to conduct their research, but their training teaches them little about the nature of scientific method itself. In Investigating the Psychological World, Brian Haig fills this gap. Drawing on behavioral science methodology, the philosophy of science, and statistical theory, Haig constructs a broad theory of scientific method that has particular relevance for the behavioral sciences. He terms this account of method the abductive theory of method (ATOM) in recognition of the importance it assigns to explanatory reasoning. ATOM offers the framework for a coherent treatment of a range of quantitative and qualitative behavioral research methods, giving equal treatment to data-analytic methods and methods of theory construction.
Haig draws on the new experimentalism in the philosophy of science to reconstruct the process of phenomena detection as it applies to psychology; he considers the logic and purpose of exploratory factor analysis; he discusses analogical modeling as a means of theory development; and he recommends the use of inference to the best explanation for evaluating theories in psychology. Finally, he outlines the nature of research problems, discusses the nature of the abductive method, and describes applications of the method to grounded theory method and clinical reasoning. The book will be of interest not only to philosophers of science but also to psychological researchers who want to deepen their conceptual understanding of research methods and methodological concerns.
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