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For much of the twentieth century scientists sought to explain objects and processes by reducing them to their components—nuclei into protons and neutrons, proteins into amino acids, and so on—but over the past forty years there has been a marked turn toward explaining phenomena by building them up rather than breaking them down. This collection reflects on the history and significance of this turn toward “growing explanations” from the bottom up. The essays show how this strategy—based on a widespread appreciation for complexity even in apparently simple processes and on the capacity of computers to simulate such complexity—has played out in a broad array of sciences. They describe how scientists are reordering knowledge to emphasize growth, change, and contingency and, in so doing, are revealing even phenomena long considered elementary—like particles and genes—as emergent properties of dynamic processes. Written by leading historians and philosophers of science, these essays examine the range of subjects, people, and goals involved in changing the character of scientific analysis over the last several decades. They highlight the alternatives that fields as diverse as string theory, fuzzy logic, artificial life, and immunology bring to the forms of explanation that have traditionally defined scientific modernity. A number of the essays deal with the mathematical and physical sciences, addressing concerns with hybridity and the materials of the everyday world. Other essays focus on the life sciences, where questions such as “What is life?” and “What is an organism?” are undergoing radical re-evaluation. Together these essays mark the contours of an ongoing revolution in scientific explanation. Contributors. David Aubin, Amy Dahan Dalmedico, Richard Doyle, Claus Emmeche, Peter Galison, Stefan Helmreich, Ann Johnson, Evelyn Fox Keller, Ilana Löwy, Claude Rosental, Alfred Tauber
For much of the twentieth century scientists sought to explain objects and processes by reducing them to their components—nuclei into protons and neutrons, proteins into amino acids, and so on—but over the past forty years there has been a marked turn toward explaining phenomena by building them up rather than breaking them down. This collection reflects on the history and significance of this turn toward “growing explanations” from the bottom up. The essays show how this strategy—based on a widespread appreciation for complexity even in apparently simple processes and on the capacity of computers to simulate such complexity—has played out in a broad array of sciences. They describe how scientists are reordering knowledge to emphasize growth, change, and contingency and, in so doing, are revealing even phenomena long considered elementary—like particles and genes—as emergent properties of dynamic processes. Written by leading historians and philosophers of science, these essays examine the range of subjects, people, and goals involved in changing the character of scientific analysis over the last several decades. They highlight the alternatives that fields as diverse as string theory, fuzzy logic, artificial life, and immunology bring to the forms of explanation that have traditionally defined scientific modernity. A number of the essays deal with the mathematical and physical sciences, addressing concerns with hybridity and the materials of the everyday world. Other essays focus on the life sciences, where questions such as “What is life?” and “What is an organism?” are undergoing radical re-evaluation. Together these essays mark the contours of an ongoing revolution in scientific explanation. Contributors. David Aubin, Amy Dahan Dalmedico, Richard Doyle, Claus Emmeche, Peter Galison, Stefan Helmreich, Ann Johnson, Evelyn Fox Keller, Ilana Löwy, Claude Rosental, Alfred Tauber
This handbook is intended as an introductory guide to students at all levels on the principles and practice of plant growth analysis. Many have found this quantitative approach to be useful in the description and interpretation of the performance of whole plant systems grown under natural, semi-natural or controlled conditions. Most of the methods described require only simple experimental data and facilities. For the classical approach, GCSE biology and mathematics (or their equivalents) are the only theoretical backgrounds required. For the functional approach, a little calculus and statistical theory is needed. All of the topics regarding the quantitative basis of productivity recently introduced to the Biology A-level syllabus by the Joint Matriculation Board are covered. The booklet replaces my elementary Plant Growth Analysis (1978, London: Edward Arnold) which is now out of print. The presentation is very basic indeed; the opening pages give only essential outlines of the main issues. They are followed by brief, standardized accounts of each growth-analytical concept taken in turn. The illustrations deal more with the properties of well-grown material than with the effects of specific environmental changes, even though that is where much of the subject's interest lies. However, detailed references to the relevant parts of more com prehensive works appear throughout, and a later section on 'Inter relations' adds perspective. Some 'Questions and answers' may also help to show what topics will arise if the subject is pursued further.
From the renowned psychologist who introduced the world to “growth mindset” comes this updated edition of the million-copy bestseller—featuring transformative insights into redefining success, building lifelong resilience, and supercharging self-improvement. “Through clever research studies and engaging writing, Dweck illuminates how our beliefs about our capabilities exert tremendous influence on how we learn and which paths we take in life.”—Bill Gates, GatesNotes “It’s not always the people who start out the smartest who end up the smartest.” After decades of research, world-renowned Stanford University psychologist Carol S. Dweck, Ph.D., discovered a simple but groundbreaking idea: the power of mindset. In this brilliant book, she shows how success in school, work, sports, the arts, and almost every area of human endeavor can be dramatically influenced by how we think about our talents and abilities. People with a fixed mindset—those who believe that abilities are fixed—are less likely to flourish than those with a growth mindset—those who believe that abilities can be developed. Mindset reveals how great parents, teachers, managers, and athletes can put this idea to use to foster outstanding accomplishment. In this edition, Dweck offers new insights into her now famous and broadly embraced concept. She introduces a phenomenon she calls false growth mindset and guides people toward adopting a deeper, truer growth mindset. She also expands the mindset concept beyond the individual, applying it to the cultures of groups and organizations. With the right mindset, you can motivate those you lead, teach, and love—to transform their lives and your own.
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
Statistical Analysis of Human Growth and Development is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. Designed for nonstatisticians and statisticians new to the analysis of growth and development data, the book collects methods scattered throughout the literature and explains how to use them to solve common research problems. It also discusses how well a method addresses a specific scientific question and how to interpret and present the analytic results. Stata is used to implement the analyses, with Stata codes and macros for generating example data sets, a detrended Q-Q plot, and weighted maximum likelihood estimation of binary items available on the book’s CRC Press web page. After reviewing research designs and basic statistical tools, the author discusses the use of existing tools to transform raw data into analyzable variables and back-transform them to raw data. He covers regression analysis of quantitative, binary, and censored data as well as the analysis of repeated measurements and clustered data. He also describes the development of new growth references and developmental indices, the generation of key variables based on longitudinal data, and the processes to verify the validity and reliability of measurement tools. Looking at the larger picture of research practice, the book concludes with coverage of missing values, multiplicity problems, and multivariable regression. Along with two simulated data sets, numerous examples from real experimental and observational studies illustrate the concepts and methods. Although the book focuses on examples of anthropometric measurements and changes in cognitive, social-emotional, locomotor, and other abilities, the ideas are applicable to many other physical and psychosocial phenomena, such as lung function and depressive symptoms.
This paper reviews the extensive empirical literature on the growth and determinants of government expenditure. Although the coverage does not aim to be exhaustive, the authors provide an overview of the quantitative approaches to analyzing the growth in government expenditure. The main debates in the literature are described, and the authors present a few tests of some theories and describe one or two of their own experiments in others. The paper highlights the data problems and the technical difficulties of hypothesis testing and model estimation in this area, many arising from the nature of the problem studied. It is contended that the quantitative analysis of government expenditure growth has often improved the formulation of hypotheses, but that data and theoretical limitations have meant that the methods employed have not always been justified.
This book is a PhD thesis that is highly relevant to anyone involved in management. It identifies and analyses in depth the key constructs of leadership, teamwork and enterprise that are vital for a successful 'growth' business. The focus is on leadership, enterprise and the make-up of senior management teams, but the research outcomes can equally be applied to any management team environment, such as committees, working groups, panels, or administrative bodies. Critically, an unsuitable leader will almost guarantee failure, so having the ability to recognise leaders that are capable of delivering success is crucial. This book is invaluable for those people who need to understand how leadership, teamwork and enterprise interact to create dynamic and highly successful management teams.
It is often claimed that we live in an expert society, a society where more and more individuals take expert roles in increasingly narrow fields. In contrast to more traditional experts most of these new experts lack generally accepted mechanisms for the certification and legitimation of their expertise. This book focuses on these new as well as established experts and the efforts undertaken to secure and legitimate their expertise. We view these efforts as organizing attempts and study them on four different levels – the society, the market, the organization and the individual. Based on empirical studies on these four levels of analysis, The Organization of the Expert Society makes the argument that current organizing initiatives in the expert society are based in an objectifying view of expertise that risks concealing and downplaying key aspects of expertise. Well-intended organizing initiatives in the expert society thus run the risk of promoting ignorance rather than securing expertise. Focusing on a current, general and global phenomenon, the rise and organization of an expert society. The Organization of the Expert Society will be key reading for scholars, academics and policy makers in the management fields of Organizational Theory, Management Consulting, Organizations & Society, Critical Management Studies as well as the disciplines of Sociology, Political Science and Social Anthropology.
The Quantum of Explanation advances a bold new theory of how explanation ought to be understood in philosophical and cosmological inquiries. Using a complete interpretation of Alfred North Whitehead’s philosophical and mathematical writings and an interpretive structure that is essentially new, Auxier and Herstein argue that Whitehead has never been properly understood, nor has the depth and breadth of his contribution to the human search for knowledge been assimilated by his successors. This important book effectively applies Whitehead’s philosophy to problems in the interpretation of science, empirical knowledge, and nature. It develops a new account of philosophical naturalism that will contribute to the current naturalism debate in both Analytic and Continental philosophy. Auxier and Herstein also draw attention to some of the most important differences between the process theology tradition and Whitehead’s thought, arguing in favor of a Whiteheadian naturalism that is more or less independent of theological concerns. This book offers a clear and comprehensive introduction to Whitehead’s philosophy and is an essential resource for students and scholars interested in American philosophy, the philosophy of mathematics and physics, and issues associated with naturalism, explanation and radical empiricism.