Written by one of the masters of the foundation of measurement, Louis Narens' new book thoroughly examines the basis for the measurement-theoretic concept of meaningfulness and presents a new theory about the role of numbers and invariance in science. The book associates with each portion of mathematical science a subject matter that the portion of science is intended to investigate or describe. It considers those quantitative or empirical assertions and relationships that belong to the subject matter to be meaningful (for that portion of science) and those that do not belong to be meaningless. The first two chapters of the Theories of Meaningfulness introduce meaningfulness concepts, their place in the history of science, and some of their traditional applications. The idea that meaningfulness will have different, but interrelated uses is then introduced. To provide formal descriptions of these, the author employs a powerful framework that incorporates pure mathematics, provides for qualitative objects and relations, and addresses the relationships between qualitative objects and pure mathematics. The framework is then applied to produce axiomatic theories of meaningfulness, including generalizations and a new foundation for the famous Erlanger Program of mathematics. The meaningfulness concept is further specialized with the introduction of intrinsicness, which deals with meaningful concepts and relations that are lawful and qualitativeness, which is concerned with qualitative concepts. The concept of empiricalness is then introduced to distinguish it from meaningfulness and qualitativeness. The failure to distinguish empiricalness from meaningfulness and qualitativeness has produced much confusion in the foundations of science literature and has generated many pseudo-controversies. This book suggests that many of these disappear when empiricalness is intersected with the other concepts to produce "meaningful and empirical relations," "empirical laws," and "qualitative and empirical concepts." A primary goal of this book is to show that the new theories of meaningfulness and intrinsicness developed in this book are not only descriptive but are also potent. Asserting that they do more than codify already existing concepts the book: *works out logical relationships between meaningfulness concepts that were previously unrecognized; *clarifies certain well-known and important debates by providing rich languages with new concepts and technical results (theorems) that yield insights into the debated issues and positions taken on them; and *provides new techniques and results in substantive scientific areas of inquiry. This book is about the role of mathematics in science. It will be useful to those concerned with the foundations of science in their respective fields. Various substantive examples from the behavioral sciences are presented.
Standard probability theory has been an enormously successful contribution to modern science. However, from many perspectives it is too narrow as a general theory of uncertainty, particularly for issues involving subjective uncertainty. This first-of-its-kind book is primarily based on qualitative approaches to probabilistic-like uncertainty, and includes qualitative theories for the standard theory as well as several of its generalizations.One of these generalizations produces a belief function composed of two functions: a probability function that measures the probabilistic strength of an uncertain event, and another function that measures the amount of ambiguity or vagueness of the event. Another unique approach of the book is to change the event space from a boolean algebra, which is closely linked to classical propositional logic, to a different event algebra that is closely linked to a well-studied generalization of classical propositional logic known as intuitionistic logic. Together, these new qualitative theories succeed where the standard probability theory fails by accounting for a number of puzzling empirical findings in the psychology of human probability judgments and decision making.
This book is designed to be an introduction to the theories of measurement and meaningfulness, and not a comprehensive study of those topics. A major theme of this book is the psychophysical measurement of subjective intensity. This has been a subject of intense interest in psychology from the very beginning of experimental psychology. And from tha
Utilitarianism began as a movement for social reform that changed the world, based on the ideal of maximizing pleasure and minimizing pain. There is a tendency to enter into debates for and against the ethical doctrine of Utilitarianism without a clear understanding of its basic concepts. The Pursuit of Happiness now offers a rigorous account of the foundations of Utilitarianism, and vividly sets out possible ways forward for its future development. To understand Utilitarianism, we must understand utility: how is it to be measured, and how the aggregate utility of a group can be understood. Louis Narens and Brian Skyrms, respectively a cognitive scientist and a philosopher, pursue these questions by adopting both formal and historical methods, examining theories of measuring utility from Jeremy Bentham, the founder of the Utilitarian movement, to the present day, taking in psychophysics, positivism, measurement theory, meaningfulness, neuropsychology, representation theorems, and the dynamics of formation of conventions. On this basis, Narens and Skyrms argue that a meaningful form of Utilitarianism that can coordinate action in social groups is possible through interpersonal comparison and the formation of conventions.
There are many books on lattice theory in the field, but none interfaces with the foundations of probability. This book does. It also develops new probability theories with rigorous foundations for decision theory and applies them to specific well-known problematic examples. There is only one other book that attempts this. It uses quantum probability theory from physics. The new probability theories developed in this book are different; they are not borrowed from physics but are explicitly designed for decision theory.
Risk Analysis: Foundations, Models, and Methods fully addresses the questions of "What is health risk analysis?" and "How can its potentialities be developed to be most valuable to public health decision-makers and other health risk managers?" Risk analysis provides methods and principles for answering these questions. It is divided into methods for assessing, communicating, and managing health risks. Risk assessment quantitatively estimates the health risks to individuals and to groups from hazardous exposures and from the decisions or activities that create them. It applies specialized models and methods to quantify likely exposures and their resulting health risks. Its goal is to produce information to improve decisions. It does this by relating alternative decisions to their probable consequences and by identifying those decisions that make preferred outcomes more likely. Health risk assessment draws on explicit engineering, biomathematical, and statistical consequence models to describe or simulate the causal relations between actions and their probable effects on health. Risk communication characterizes and presents information about health risks and uncertainties to decision-makers and stakeholders. Risk management applies principles for choosing among alternative decision alternatives or actions that affect exposure, health risks, or their consequences.
This book examines the basis for measurement- how to measure what we measure and the meaning of what we measure. It is expected to appeal to those interested in measurement in the fields of psych, econ, med, edu, soc, & other applied social sciences.
Utilitarianism began as a movement for social reform that changed the world, based on the ideal of maximizing pleasure and minimizing pain. There is a tendency to enter into debates for and against the ethical doctrine of Utilitarianism without a clear understanding of its basic concepts. The Pursuit of Happiness now offers a rigorous account of the foundations of Utilitarianism, and vividly sets out possible ways forward for its future development. To understand Utilitarianism, we must understand utility: how is it to be measured, and how the aggregate utility of a group can be understood. Louis Narens and Brian Skyrms, respectively a cognitive scientist and a philosopher, pursue these questions by adopting both formal and historical methods, examining theories of measuring utility from Jeremy Bentham, the founder of the Utilitarian movement, to the present day, taking in psychophysics, positivism, measurement theory, meaningfulness, neuropsychology, representation theorems, and the dynamics of formation of conventions. On this basis, Narens and Skyrms argue that a meaningful form of Utilitarianism that can coordinate action in social groups is possible through interpersonal comparison and the formation of conventions.
This book is designed to be an introduction to the theories of measurement and meaningfulness, and not a comprehensive study of those topics. A major theme of this book is the psychophysical measurement of subjective intensity. This has been a subject of intense interest in psychology from the very beginning of experimental psychology. And from tha
There are many books on lattice theory in the field, but none interfaces with the foundations of probability. This book does. It also develops new probability theories with rigorous foundations for decision theory and applies them to specific well-known problematic examples. There is only one other book that attempts this. It uses quantum probability theory from physics. The new probability theories developed in this book are different; they are not borrowed from physics but are explicitly designed for decision theory.
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