Search Results

Networks, Diffusion, and Cycles of Collective Action

Pamela E. Oliver and Daniel J. Myers

in Social Movements and Networks: Relational Approaches to Collective Action

Uses simulation models to explore network mechanisms in diffusion processes and protest cycles. The network dimension is taken into account, focusing on three processes: information flows, influence ... More

Uses simulation models to explore network mechanisms in diffusion processes and protest cycles. The network dimension is taken into account, focusing on three processes: information flows, influence flows, and the construction of joint action. The repeatable and reversible nature of protest requires models of diffusion that focus on the spread of actions and not the spread of ideas across actors. Moreover, while diffusion processes tend to generate waves or cycles of events, not all waves of events arise from diffusion processes. The effect of network structure varies greatly depending upon the nature of a particular network process.Less

Modeling Health: The Role of Simulation Models in Health Information Systems

Michael C. Wolfson

in Health Statistics: Shaping policy and practice to improve the population's health

This chapter argues for the expansion of the uses of health statistics to include the construction of simulation models. Simulation models can help policymakers to address “what if” questions in the ... More

This chapter argues for the expansion of the uses of health statistics to include the construction of simulation models. Simulation models can help policymakers to address “what if” questions in the formulation of new health policies and to explore the causal relationships inherent in answers to those questions. To facilitate the increased use of health statistics for simulation modeling, the importance of fulfilling two needs are emphasized: first, the need for coherent frameworks for collecting the data that become health statistics; and second, the need to use electronic health records for the generation of health statistics.Less

Hybrid Simulation Modeling in Population Health

Sally C. Brailsford, Dave C. Evenden, and Joe Viana

in Complex Systems and Population Health

Hybrid simulation is particularly useful in population health, since healthcare systems are characterized by both dynamic and stochastic complexity and the use of one single simulation approach may ... More

Hybrid simulation is particularly useful in population health, since healthcare systems are characterized by both dynamic and stochastic complexity and the use of one single simulation approach may result in an oversimplified model that fails to address the real problem. This chapter presents the foundational concepts of hybrid simulation modeling and describes how the various stages in developing a single-method model can be adapted for hybrid simulation. These are illustrated by two examples from population health: age-related macular degeneration and dementia. In both cases, hybrid simulation has enabled the model to reflect the complexity of the decisions facing population health planners, who have to consider individual patient variability and the uncertainty of health outcomes from a “whole-system” perspective. The chapter presents a set of guidelines for modelers, showing how an integrated, multiscale simulation modeling framework can be developed, validated, and exploited for population health problems. The integration of micro-level modeling with macro-level modeling approaches, grounded in foundational complex systems properties and theories, can capture aspects of health systems that a single-method approach cannot.Less

Introduction

Johannes Lenhard

in Calculated Surprises: A Philosophy of Computer Simulation

The chapter provides a brief overview of the history of simulation modeling and of philosophical accounts dealing with simulation. Computer and simulation modeling, it is stated, do form a new ... More

The chapter provides a brief overview of the history of simulation modeling and of philosophical accounts dealing with simulation. Computer and simulation modeling, it is stated, do form a new exploratory and iterative type of mathematical modeling. Four aspects are introduced: experiment and artificiality, visualization, plasticity, and epistemic opacity. The key thesis is that the novelty of simulation modeling rests on how these aspects are combined into a combinatorial style of reasoning. The computer as an instrument does not only speed up calculations but also channels mathematical modeling. This is exerting transformational power on central concepts like solution, validation, and the real—instrumental divide.Less

Model Thinking and Formal Modeling to Improve Our Mental Models in Population Health Research

Michael K. Lemke

in Complex Systems and Population Health

When encountering complex systems, the human mind applies various heuristics, and from these heuristics, mental models—how people understand phenomena in the real world—emerge, which shape their ... More

When encountering complex systems, the human mind applies various heuristics, and from these heuristics, mental models—how people understand phenomena in the real world—emerge, which shape their decisions. Unfortunately, the same limitations that confound heuristics similarly cloud people’s mental models and result in fundamental misunderstandings and lead to flawed decisions. The development of models, through the act of modeling, provide means to mitigate inherent shortcomings in people’s cognitive abilities and mental models and can stimulate new ways of understanding and acting in population health, grounded in model thinking. For the study of complex systems in particular, computational simulation modeling approaches enable novel scientific inquiry and facilitate decision-making. Engagement in modeling can also overcome the difficulties in learning imposed by complex systems, leading to transformed mental models and the proliferation of model thinking in population health research and action.Less

Approaches to Modeling Cities and Regions

Roger White, Guy Engelen, and Inge Uljee

in Modeling Cities and Regions As Complex Systems: From Theory to Planning Applications

The modelling of urban and regional structure has a long history, with the land use model of Von Thunen, the central place theories of Christaller and Losch, and the industrial location model of ... More

The modelling of urban and regional structure has a long history, with the land use model of Von Thunen, the central place theories of Christaller and Losch, and the industrial location model of Weber providing the basis for the development of a mathematical location theory. For the most part, however, the equations could not be solved analytically without making unrealistic simplifying assumptions, so the results, like the concentric zones of the urban spatial structure models, were also unrealistic; one consequence was a shift away from mathematical modelling to inferential statistics and various postmodernist approaches. Another was the introduction of simulation modelling, especially of urban spatial structure, with agent based and CA based models being the preferred approaches. The models of Peter Allen, Juval Portugali and Izhak Benenson, Denise Pumain, Xia Li, and Keith Clarke are among the most important. The models of this book also belong with this group.Less

Modeling Plant and Animal Productivity and Fuel Use

C. David Johnson and Timothy A. Kohler

in Emergence and Collapse of Early Villages: Models of Central Mesa Verde Archaeology

Realistic simulation of long-term household settlement patterns is based on spatially and temporally variable supplies of critical natural resources produced by study-area soils. Annual net primary ... More

Realistic simulation of long-term household settlement patterns is based on spatially and temporally variable supplies of critical natural resources produced by study-area soils. Annual net primary productivity of native vegetation modulated by variability through time in precipitationprovides the basis for estimating supplies of fuelwood and high-quality animal protein required for successful human habitation in this area. This chapter describes soils in Village Ecodynamics Project study area; the native vegetation they supported; the number of deer, hare, and rabbit supported by the vegetation; and the methods by which agents in the simulation harvest fuelwood. Depletion of readily available fuelwood may have influenced long-term human behaviors related to architectural designs and settlement distributions.Less

Reliability without Truth

in Science in the Age of Computer Simulation

This chapter examines the source of credibility of computer simulation models. It suggests that the practice of using fictions in building credible simulations is worthy of closer scrutiny by ... More

This chapter examines the source of credibility of computer simulation models. It suggests that the practice of using fictions in building credible simulations is worthy of closer scrutiny by philosophers of science interested in the various arguments for and against scientific realism. The chapter analyzes two examples of fictions from the field of computational fluid dynamics—so-called artificial viscosity and vorticity confinement—arguing that these kinds of model-building techniques are counterexamples to the doctrine that success implies truth.Less

Modeling the Dynamics of A Forest Giant

David R. Foster (ed.)

in Hemlock: A Forest Giant on the Edge

This chapter discusses the use of simulation models to address ecological questions. Ecological modelling refers to computer simulations of ecological processses represented and linked together using ... More

This chapter discusses the use of simulation models to address ecological questions. Ecological modelling refers to computer simulations of ecological processses represented and linked together using mathematical and statistical functions. These models enable scientists to generate hypotheses about the ways ecosystems work. The chapter focuses on a forest model that has been used to anticipate the effects of adelgid-induced deaths of hemlocks in eastern North America.Less

When Theories Shake Hands

in Science in the Age of Computer Simulation

This chapter explores the theories used in computer simulation. It suggests that there is a class of computer simulation models that are especially important to philosophers interested in the ... More

This chapter explores the theories used in computer simulation. It suggests that there is a class of computer simulation models that are especially important to philosophers interested in the relations between theories at different levels of description. These are the so-called parallel multiscale simulation models, which are cobbled together using the resources of quantum mechanics, classical molecular dynamics, and the linear-elastic theory of solids. The chapter explains how it is possible for these different theoretical frameworks, which provide essentially incompatible descriptions of the underlying structure of the systems they describe, to be combined together.Less

Validation of Microsimulation Models Used for Population Health Policy

Fernando Alarid-Escudero, Roman Gulati, and Carolyn M. Rutter

in Complex Systems and Population Health

This chapter discusses validation of simulation models used to inform health policy. Confidence in a model’s validity can be weaker or stronger depending on several factors. These factors include ... More

This chapter discusses validation of simulation models used to inform health policy. Confidence in a model’s validity can be weaker or stronger depending on several factors. These factors include verifying whether model specifications were implemented correctly, evaluating the extent to which model-predicted results are consistent with empirical results, and examining whether model predictions are robust to alternative structural assumptions. Systematic evaluation of these factors can be used to gauge the extent to which a model is validated for a given application. It reviews types of validation, discusses the related concepts of calibration and nonidentifiability, takes a deeper dive into cancer model validation studies, and concludes with questions that consumers of models should ask (and modelers should answer) to inform judgment about a model’s fitness for purpose. Final judgments about when model results can be trusted ultimately rely on the evolving understanding of the disease and intervention effects, available data relevant to the application, and access to reporting of model validation exercises.Less

The World in a Machine: Origins and Impacts of Early Computerized Global Systems Models

Paul N. Edwards

in Systems, Experts, and Computers: The Systems Approach in Management and Engineering, World War II and After

This chapter explores the origins of two types of simulation models, namely numerical models of weather and climate, and world-dynamics models that are offshoots of a general method known as “system ... More

This chapter explores the origins of two types of simulation models, namely numerical models of weather and climate, and world-dynamics models that are offshoots of a general method known as “system dynamics.” By the 1960s, increasing computer power made possible detailed simulations of the general circulation of Earth’s atmosphere. This allowed scientists to simulate weather and climate—genuinely global systems. Computer pioneer Jay Forrester created techniques for simulating the dynamic behavior of large socio-technical systems during approximately the same period. He began in the late 1950s with factories, then proceeded to cities, eventually publishing a book on the general “principles of systems” in 1968, and finally, modeled “world dynamics” in the early 1970s. Under Forrester’s tutelage, the MIT System Dynamics Group used world-dynamics models as the basis for the controversial bestseller The Limits to Growth.Less

Wealth Accumulation by Age Cohort: The Role of Savings, Capital Gains, and Intergenerational Transfers

Edward N. Wolff

in Inheriting Wealth in America: Future Boom or Bust?

Chapter 5 makes use of the so-called indirect method discussed in the literature review to analyze the role of inheritances and other intergenerational transfers on the wealth accumulation of ... More

Chapter 5 makes use of the so-called indirect method discussed in the literature review to analyze the role of inheritances and other intergenerational transfers on the wealth accumulation of households. A simulation model is developed to calibrate the quantitative importance of intergenerational transfers and other sources of household wealth over the period from 1983 to 2007. Two issues receive particular attention. First, for individual age groups, what are the relative contributions made to wealth accumulation of (i) savings out of income, (ii) capital gains on wealth, (iii) inheritances, and (iv) inter-vivos transfers? Second, what is the relative importance of intergenerational transfers versus savings in the lifetime accumulation of wealth? The major finding is that over the lifetime, about one-third of household wealth accumulation can be traced to household savings, another third to inheritances, and the remaining third to inter-vivos transfers.Less

Models of Climate: Values and Uncertainties

in Science in the Age of Computer Simulation

This chapter, which focuses on simulation models of climate and its future, investigates whether it is reasonable to expect climate modelers to exclude non-epistemic values from the internal aspects ... More

This chapter, which focuses on simulation models of climate and its future, investigates whether it is reasonable to expect climate modelers to exclude non-epistemic values from the internal aspects of their research. It suggests that there are at least two features of climate models that make them worthy of special attention from the point of view of philosophy of science. The first is that the extremely complex modularity of global climate models leads to a novel kind of epistemological holism, and the second is that climate simulations have enormous public policy implications. The chapter also discusses the opposing arguments of Richard Rudner and Richard Jeffrey about inductive risk.Less

Construing Climate Change

John Frow

in On Interpretive Conflict

Chapter Four discusses the roles played in undermining the science of climate change by the denialist counter-institutions of knowledge funded by the fossil-fuel industries, and particularly the way ... More

Chapter Four discusses the roles played in undermining the science of climate change by the denialist counter-institutions of knowledge funded by the fossil-fuel industries, and particularly the way those institutions have reduced the science of climate change to a proxy in broader economic and political struggles. One of the charges frequently made by denialists is that climate science does not correspond with the observed data. One of the central arguments of this chapter covers the relation between scientific models and a “reality” that is only indirectly available to them and that is configured in a form that is amenable to analysis. The chapter also argues that the epistemic solidity of the craft of modeling can thus not be derived from its access to and reflection of a field of independently given data. Rather, it is a function of a rigorous regime of knowledge and of the convergence of many different models on an explanation of climate change that directly implies the effect of greenhouse gases. More generally, modeling is a convergence of the resources and constraints of the institution of science, which should be understood as a normative apparatus and as a field deeply entangled with the imperatives of capitalism.Less

Introduction

in Science in the Age of Computer Simulation

This introduction discusses the theme of this book, which is about computer simulation and the philosophy of science. The book examines what philosophers of science should learn in the age of ... More

This introduction discusses the theme of this book, which is about computer simulation and the philosophy of science. The book examines what philosophers of science should learn in the age of simulation and what philosophy can contribute to our understanding of how the digital computer is transforming science. It investigates the relationship between computer simulation and experiment, the conditions under which computer simulation can be reliable, and the role of deliberately false assumptions in the construction of simulation models.Less

System Dynamics Modeling to Rethink Health System Reform

Jack Homer, Bobby Milstein, and Gary B. Hirsch

in Complex Systems and Population Health

The Rethink Health Dynamics Model represents the complex dynamics of a regional health system in the United States and has been calibrated for more than 10 regions using nationwide and local data. ... More

The Rethink Health Dynamics Model represents the complex dynamics of a regional health system in the United States and has been calibrated for more than 10 regions using nationwide and local data. When testing single interventions, the simulated improvement in system performance is often less than desired. By experimenting with combinations of interventions, the authors have identified recurring reasons for underperformance or intervention pitfalls. Here they discuss four common pitfalls and possible ways to overcome each with additional intervention. The pitfalls include (a) trying to cut costs without changing payment incentives; (b) depleting available funds without securing sustainable financing; (c) trying to achieve greater equity through service delivery without building capacity to meet greater demand; and (d) missing the opportunity to achieve multiple goals simultaneously through the use of mutually supporting interventions. The chapter illustrates each pitfall and proposed solution with causal feedback diagrams and simulation output graphs.Less

Smooth Landing or Crash?: Model-Based Scenarios of Global Current Account Rebalancing

Hamid Faruqee, Douglas Laxton, Dirk Muir, and Paolo A. Pesenti

in G7 Current Account Imbalances: Sustainability and Adjustment

This chapter employs a sophisticated new open economy multicountry simulation model to examine different scenarios for global current account adjustment. The analysis indicates that ... More

This chapter employs a sophisticated new open economy multicountry simulation model to examine different scenarios for global current account adjustment. The analysis indicates that competition-friendly structural policies could play a prominent role in reducing current account imbalances on a sustainable basis if they were linked with a sustained increase in growth and a permanent downward shift in the net foreign asset positions of Europe and Japan. Japan and the euro area are relatively stable in terms of adjustment. US fiscal consolidation would not be obtained without some short-run costs for output growth. Europe and Japan could meaningfully add to the multilateral adjustment process through stronger pursuit of growth-enhancing structural reforms that align with their own national interests. Labor market reforms alone might not significantly contribute to rebalancing.Less