If everyone now agrees that human traits arise not from nature or nurture but from the interaction of nature and nurture, why does the “nature versus nurture” debate persist? In Beyond Versus, James Tabery argues that the persistence stems from a century-long struggle to understand the interaction of nature and nurture—a struggle to define what the interaction of nature and nurture is, how it should be investigated, and what counts as evidence for it.
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.
Many books explain what is known about the universe. This book investigates what cannot be known. Rather than exploring the amazing facts that science, mathematics, and reason have revealed to us, this work studies what science, mathematics, and reason tell us cannot be revealed. In The Outer Limits of Reason, Noson Yanofsky considers what cannot be predicted, described, or known, and what will never be understood. He discusses the limitations of computers, physics, logic, and our own thought processes.
In the 1930s a series of seminal works published by Alan Turing, Kurt Gödel, Alonzo Church, and others established the theoretical basis for computability. This work, advancing precise characterizations of effective, algorithmic computability, was the culmination of intensive investigations into the foundations of mathematics. In the decades since, the theory of computability has moved to the center of discussions in philosophy, computer science, and cognitive science.
Our intuitive assumption that only organisms are the real individuals in the natural world is at odds with developments in cell biology, ecology, genetics, evolutionary biology, and other fields. Although organisms have served for centuries as nature’s paradigmatic individuals, science suggests that organisms are only one of the many ways in which the natural world could be organized. When living beings work together—as in ant colonies, beehives, and bacteria-metazoan symbiosis—new collective individuals can emerge.
This collection reports on the latest research on an increasingly pivotal issue for evolutionary biology: cooperation. The chapters are written from a variety of disciplinary perspectives and utilize research tools that range from empirical survey to conceptual modeling, reflecting the rich diversity of work in the field. They explore a wide taxonomic range, concentrating on bacteria, social insects, and, especially, humans.
Contemporary discussions of the success of science often invoke an ancient metaphor from Plato's Phaedrus: successful theories should "carve nature at its joints." But is nature really "jointed"? Are there natural kinds of things around which our theories cut? The essays in this volume offer reflections by a distinguished group of philosophers on a series of intertwined issues in the metaphysics and epistemology of classification.
Each of us is a collection of more than ten trillion cells, busy performing tasks crucial to our continued existence. Gene regulation networks, consisting of a subset of genes called transcription factors, control cellular activity, producing the right gene activities for the many situations that the multiplicity of cells in our bodies face. Genes working together make up a truly ingenious system. In this book, Roger Sansom investigates how gene regulation works and how such a refined but simple system evolved.
Information shapes biological organization in fundamental ways and at every organizational level. Because organisms use information--including DNA codes, gene expression, and chemical signaling--to construct, maintain, repair, and replicate themselves, it would seem only natural to use information-related ideas in our attempts to understand the general nature of living systems, the causality by which they operate, the difference between living and inanimate matter, and the emergence, in some biological species, of cognition, emotion, and language.
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.