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A philosopher subjects the claims of evolutionary psychology to the evidential and methodological requirements of evolutionary biology, concluding that evolutionary psychology's explanations amount to speculation disguised as results. Human beings, like other organisms, are the products of evolution. Like other organisms, we exhibit traits that are the product of natural selection. Our psychological capacities are evolved traits as much as are our gait and posture. This much few would dispute. Evolutionary psychology goes further than this, claiming that our psychological traits--including a wide variety of traits, from mate preference and jealousy to language and reason--can be understood as specific adaptations to ancestral Pleistocene conditions. In Evolutionary Psychology as Maladapted Psychology, Robert Richardson takes a critical look at evolutionary psychology by subjecting its ambitious and controversial claims to the same sorts of methodological and evidential constraints that are broadly accepted within evolutionary biology. The claims of evolutionary psychology may pass muster as psychology; but what are their evolutionary credentials? Richardson considers three ways adaptive hypotheses can be evaluated, using examples from the biological literature to illustrate what sorts of evidence and methodology would be necessary to establish specific evolutionary and adaptive explanations of human psychological traits. He shows that existing explanations within evolutionary psychology fall woefully short of accepted biological standards. The theories offered by evolutionary psychologists may identify traits that are, or were, beneficial to humans. But gauged by biological standards, there is inadequate evidence: evolutionary psychologists are largely silent on the evolutionary evidence relevant to assessing their claims, including such matters as variation in ancestral populations, heritability, and the advantage offered to our ancestors. As evolutionary claims they are unsubstantiated. Evolutionary psychology, Richardson concludes, may offer a program of research, but it lacks the kind of evidence that is generally expected within evolutionary biology. It is speculation rather than sound science--and we should treat its claims with skepticism.
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Complexiteit (Filosofie) --- Complexity (Philosophy) --- Complexité (Philosophie) --- Decomposition (Methode mathematique) --- Decomposition method --- Localisatie-theorie --- Localisation [Theorie de la ] --- Localization theory --- Ontbinding (Wiskundige methode) --- Research --- Decomposition method. --- Localization theory. --- Methodology. --- -Science --- Science research --- Scientific research --- Information services --- Learning and scholarship --- Methodology --- Research teams --- Categories (Mathematics) --- Homotopy theory --- Nilpotent groups --- Method, Decomposition --- Operations research --- Programming (Mathematics) --- System analysis --- Philosophy --- Emergence (Philosophy) --- -Methodology --- Complexity (Philosophy). --- -Categories (Mathematics) --- Science --- -Method, Decomposition --- Research - Methodology. --- Philosophy of science
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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.
Research --- Decomposition method --- Localization theory --- Complexity (Philosophy) --- Methodology --- Decomposition method. --- Localization theory. --- Methodology. --- 168.5 --- Multidisciplinair karakter der wetenschappen --- Categories (Mathematics) --- Homotopy theory --- Nilpotent groups --- Method, Decomposition --- Operations research --- Programming (Mathematics) --- System analysis --- Philosophy --- Emergence (Philosophy) --- Recherche --- Décomposition (méthode mathématique) --- Localisation, Théorie de la --- Complexité (philosophie) --- methodologie --- Décomposition (méthode mathématique) --- Localisation, Théorie de la --- Complexité (philosophie)
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"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"--MIT CogNet.
Research --- Decomposition method. --- Localization theory. --- Complexity (Philosophy) --- Decomposition method --- Localization theory --- Physical Sciences & Mathematics --- Sciences - General --- Methodology. --- Methodology --- Method, Decomposition --- Philosophy --- Emergence (Philosophy) --- Categories (Mathematics) --- Homotopy theory --- Nilpotent groups --- Operations research --- Programming (Mathematics) --- System analysis --- PHILOSOPHY/Philosophy of Science & Technology --- Philosophy of science --- Research - Methodology. --- Research - Methodology
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538.9 --- Condensed matter --- -Low temperatures --- -536.483 --- 536.51 --- Cryogenics --- Low temperature physics --- Temperatures, Low --- Temperature --- Cold --- Condensed materials --- Condensed media --- Condensed phase --- Materials, Condensed --- Media, Condensed --- Phase, Condensed --- Liquids --- Matter --- Solids --- Physics of condensed matter (in liquid state and solid state) --- Experiments --- -Technique --- Very low temperatures. Cryogenics --- Thermometry and thermometers in general --- 536.51 Thermometry and thermometers in general --- 536.483 Very low temperatures. Cryogenics --- 538.9 Physics of condensed matter (in liquid state and solid state) --- Low temperatures --- 536.483 --- Experiments&delete& --- Technique --- Low temperature
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