Phillip Wolff
- Published in print:
- 2008
- Published Online:
- May 2008
- ISBN:
- 9780195188370
- eISBN:
- 9780199870462
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195188370.003.0023
- Subject:
- Psychology, Cognitive Neuroscience
We use our knowledge of causal relationships to imagine possible events. We also use these relationships to look deep into the past and infer events that were not witnessed or to infer what can not ...
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We use our knowledge of causal relationships to imagine possible events. We also use these relationships to look deep into the past and infer events that were not witnessed or to infer what can not be directly seen in the present. Knowledge of causal relationships allows us to go beyond the here and now. This chapter introduces a new theoretical framework for how this very basic concept might be mentally represented. It proposes an epistemological theory of causation — that is, a theory that specifies the nature of people's knowledge of causation, the notion of causation used in everyday language and reasoning.Less
We use our knowledge of causal relationships to imagine possible events. We also use these relationships to look deep into the past and infer events that were not witnessed or to infer what can not be directly seen in the present. Knowledge of causal relationships allows us to go beyond the here and now. This chapter introduces a new theoretical framework for how this very basic concept might be mentally represented. It proposes an epistemological theory of causation — that is, a theory that specifies the nature of people's knowledge of causation, the notion of causation used in everyday language and reasoning.
Alfred Greiner and Willi Semmler
- Published in print:
- 2008
- Published Online:
- September 2008
- ISBN:
- 9780195328233
- eISBN:
- 9780199869985
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195328233.003.0005
- Subject:
- Economics and Finance, Development, Growth, and Environmental
The growth model with environmental pollution and productive public capital analyzed in Chapter 2 was characterized by local and global determinacy. However, this result may have been derived due to ...
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The growth model with environmental pollution and productive public capital analyzed in Chapter 2 was characterized by local and global determinacy. However, this result may have been derived due to the assumptions made, especially concerning the utility function of the household. This chapter allows for a more general utility function and then gives a complete characterization of the dynamics of the model. It also contributes to the literature on the dynamics of competitive economies with externalities.Less
The growth model with environmental pollution and productive public capital analyzed in Chapter 2 was characterized by local and global determinacy. However, this result may have been derived due to the assumptions made, especially concerning the utility function of the household. This chapter allows for a more general utility function and then gives a complete characterization of the dynamics of the model. It also contributes to the literature on the dynamics of competitive economies with externalities.
C. M. Roland
- Published in print:
- 2011
- Published Online:
- September 2011
- ISBN:
- 9780199571574
- eISBN:
- 9780191728976
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199571574.003.0007
- Subject:
- Physics, Condensed Matter Physics / Materials
Most polymer blends are phase-segregated, and among thermodynamically miscible blends, only a few have components that are both rubbers. Since the equilibrium morphology of miscible blends is ...
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Most polymer blends are phase-segregated, and among thermodynamically miscible blends, only a few have components that are both rubbers. Since the equilibrium morphology of miscible blends is homogeneous down to the segmental level, they can exhibit unusual properties. The focus of this chapter is the phenomena seen in miscible rubbery blends that have no counterpart in neat materials. These properties include dynamic heterogeneity, anomalous concentration dependences, and the emergence of new relaxation peaks. There are a number of models for the segmental dynamics of blends, and these are reviewed. Selected aspects of phase-separated blends are discussed briefly at the chapter’s end.Less
Most polymer blends are phase-segregated, and among thermodynamically miscible blends, only a few have components that are both rubbers. Since the equilibrium morphology of miscible blends is homogeneous down to the segmental level, they can exhibit unusual properties. The focus of this chapter is the phenomena seen in miscible rubbery blends that have no counterpart in neat materials. These properties include dynamic heterogeneity, anomalous concentration dependences, and the emergence of new relaxation peaks. There are a number of models for the segmental dynamics of blends, and these are reviewed. Selected aspects of phase-separated blends are discussed briefly at the chapter’s end.
Paul N. Edwards
- Published in print:
- 2000
- Published Online:
- August 2013
- ISBN:
- 9780262082853
- eISBN:
- 9780262275873
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262082853.003.0009
- Subject:
- Philosophy, Philosophy of Science
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 ...
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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
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.
Douglas A. Luke, Alexandra B. Morshed, Virginia R. McKay, and Todd B. Combs
- Published in print:
- 2017
- Published Online:
- November 2017
- ISBN:
- 9780190683214
- eISBN:
- 9780190683245
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190683214.003.0010
- Subject:
- Public Health and Epidemiology, Public Health
As we have seen, numerous analysis and modeling tools that take into account the natural complexity of systems and dissemination and implementation processes are available, and the use of them is ...
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As we have seen, numerous analysis and modeling tools that take into account the natural complexity of systems and dissemination and implementation processes are available, and the use of them is increasing over time. This chapter summarizes the characteristics, potential insights, and limitations of each modeling approach. It is important to note that modeling from a systems perspective, like all modeling approaches, requires assumptions about variables to include (or exclude), and hypothesized relationships dictate the quality of the model and the utility of the results. As such, using theory and empirical data to inform model design is paramount. Systems thinking and methods remain underutilized in dissemination and implementation despite demonstrations of the utility of incorporating systems thinking and methods into dissemination and implementation studies.Less
As we have seen, numerous analysis and modeling tools that take into account the natural complexity of systems and dissemination and implementation processes are available, and the use of them is increasing over time. This chapter summarizes the characteristics, potential insights, and limitations of each modeling approach. It is important to note that modeling from a systems perspective, like all modeling approaches, requires assumptions about variables to include (or exclude), and hypothesized relationships dictate the quality of the model and the utility of the results. As such, using theory and empirical data to inform model design is paramount. Systems thinking and methods remain underutilized in dissemination and implementation despite demonstrations of the utility of incorporating systems thinking and methods into dissemination and implementation studies.
Tina Saebi
- Published in print:
- 2015
- Published Online:
- April 2015
- ISBN:
- 9780198701873
- eISBN:
- 9780191771606
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198701873.003.0008
- Subject:
- Business and Management, Innovation, Strategy
Putting forward a contingency framework, this chapter examines how firms need to modify their business model in response to different threats in the business environment. Examining three different ...
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Putting forward a contingency framework, this chapter examines how firms need to modify their business model in response to different threats in the business environment. Examining three different forms business model dynamics, namely business model evolution, adaptation, and innovation, the chapter addresses the questions which environmental conditions prompt which type of business model change and by means of which capabilities firms can support change in their business models. The chapter argues and demonstrates how and why a fit between business model dynamics, environmental change and dynamic capabilities is likely to be an important antecedent to firm performance. The chapter concludes that further empirical research is required.Less
Putting forward a contingency framework, this chapter examines how firms need to modify their business model in response to different threats in the business environment. Examining three different forms business model dynamics, namely business model evolution, adaptation, and innovation, the chapter addresses the questions which environmental conditions prompt which type of business model change and by means of which capabilities firms can support change in their business models. The chapter argues and demonstrates how and why a fit between business model dynamics, environmental change and dynamic capabilities is likely to be an important antecedent to firm performance. The chapter concludes that further empirical research is required.
Abraham Bers
- Published in print:
- 2016
- Published Online:
- November 2016
- ISBN:
- 9780199295784
- eISBN:
- 9780191749063
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199295784.003.0003
- Subject:
- Physics, Nuclear and Plasma Physics, Particle Physics / Astrophysics / Cosmology
This chapter continues the discussion of collective dynamics in plasmas by exploring linear collective modes, as well as some of their nonlinear couplings. The modes are derived from simplified ...
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This chapter continues the discussion of collective dynamics in plasmas by exploring linear collective modes, as well as some of their nonlinear couplings. The modes are derived from simplified one-dimensional (one-d), reduced hydrodynamic models of plasma dynamics. In particular, the single-fluid MHD model and the two- (or multi-) fluid cold-plasma or plasma with isotropic thermal pressures models are examined here. The simplest collective modes are derived from wave equations that arise from the self-consistent field (SCF) equations of the particular plasma dynamics model in conjunction with the appropriate set of Maxwell field equations. Generally, the dynamics of plasmas is nonlinear, and the study of physically-confined plasmas must include effects of spatial inhomogeneity and boundedness of their equilibria. Some simple aspects of nonlinearity and inhomogeneity can usefully be described in terms of coupling of linear natural modes. The chapter aims at introducing descriptions of the simplest linear natural modes exhibited by hydrodynamic models of plasma dynamics.Less
This chapter continues the discussion of collective dynamics in plasmas by exploring linear collective modes, as well as some of their nonlinear couplings. The modes are derived from simplified one-dimensional (one-d), reduced hydrodynamic models of plasma dynamics. In particular, the single-fluid MHD model and the two- (or multi-) fluid cold-plasma or plasma with isotropic thermal pressures models are examined here. The simplest collective modes are derived from wave equations that arise from the self-consistent field (SCF) equations of the particular plasma dynamics model in conjunction with the appropriate set of Maxwell field equations. Generally, the dynamics of plasmas is nonlinear, and the study of physically-confined plasmas must include effects of spatial inhomogeneity and boundedness of their equilibria. Some simple aspects of nonlinearity and inhomogeneity can usefully be described in terms of coupling of linear natural modes. The chapter aims at introducing descriptions of the simplest linear natural modes exhibited by hydrodynamic models of plasma dynamics.
Ana V. Diez Roux and Ivana Stankov
- Published in print:
- 2020
- Published Online:
- October 2020
- ISBN:
- 9780190885304
- eISBN:
- 9780190885335
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190885304.003.0011
- Subject:
- Public Health and Epidemiology, Epidemiology, Public Health
This chapter reviews ways the concepts and tools of systems approaches can help understand how city environments affect health and identify the most effective policies. The authors discuss basic ...
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This chapter reviews ways the concepts and tools of systems approaches can help understand how city environments affect health and identify the most effective policies. The authors discuss basic conceptual elements of systems thinking, review core systems modeling methods, and provide examples of their applications in urban health. They conclude with a discussion of the challenges involved in using these approaches.Less
This chapter reviews ways the concepts and tools of systems approaches can help understand how city environments affect health and identify the most effective policies. The authors discuss basic conceptual elements of systems thinking, review core systems modeling methods, and provide examples of their applications in urban health. They conclude with a discussion of the challenges involved in using these approaches.
P. Houtekamer
- Published in print:
- 2014
- Published Online:
- March 2015
- ISBN:
- 9780198723844
- eISBN:
- 9780191791185
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198723844.003.0010
- Subject:
- Physics, Geophysics, Atmospheric and Environmental Physics
In this chapter, an experimental environment built around the Lorenz III toy model is used to demonstrate some points concerning localization. In an ensemble Kalman filter, localization is almost ...
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In this chapter, an experimental environment built around the Lorenz III toy model is used to demonstrate some points concerning localization. In an ensemble Kalman filter, localization is almost always necessary because of restrictions on the size of the ensembles. In fact, localization is the key technique that makes the ensemble approximation to the Kalman filter computationally feasible. How localization is best applied depends on aspects of the model dynamics and the observational network. A reasonable choice often leads to a substantial improvement in performance. Fortunately, as shown in this chapter, the statistics from the ensemble itself can provide guidance in the selection of a reasonable localization method.Less
In this chapter, an experimental environment built around the Lorenz III toy model is used to demonstrate some points concerning localization. In an ensemble Kalman filter, localization is almost always necessary because of restrictions on the size of the ensembles. In fact, localization is the key technique that makes the ensemble approximation to the Kalman filter computationally feasible. How localization is best applied depends on aspects of the model dynamics and the observational network. A reasonable choice often leads to a substantial improvement in performance. Fortunately, as shown in this chapter, the statistics from the ensemble itself can provide guidance in the selection of a reasonable localization method.
Harold L. Cole
- Published in print:
- 2020
- Published Online:
- April 2020
- ISBN:
- 9780190076030
- eISBN:
- 9780190076078
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190076030.003.0001
- Subject:
- Economics and Finance, Econometrics, Macro- and Monetary Economics
Introduces the text and lays out the vision as to what is to be covered and how this will be done. The chapter discusses the role of quantitative analysis in policy debates and how the text will ...
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Introduces the text and lays out the vision as to what is to be covered and how this will be done. The chapter discusses the role of quantitative analysis in policy debates and how the text will prepare the reader to engage in and understand these debates in Macroeconomics.Less
Introduces the text and lays out the vision as to what is to be covered and how this will be done. The chapter discusses the role of quantitative analysis in policy debates and how the text will prepare the reader to engage in and understand these debates in Macroeconomics.
Gila Sher
- Published in print:
- 2016
- Published Online:
- August 2016
- ISBN:
- 9780198768685
- eISBN:
- 9780191822032
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198768685.003.0004
- Subject:
- Philosophy, Metaphysics/Epistemology, Logic/Philosophy of Mathematics
The chapter focuses on the dynamics of the model of knowledge delineated in Chapter 3. Epistemic units move across the model along two axes: context and time. Contextual movement is due to variations ...
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The chapter focuses on the dynamics of the model of knowledge delineated in Chapter 3. Epistemic units move across the model along two axes: context and time. Contextual movement is due to variations in perspective and to a multiplicity of factors concerning both the world and the knower. Temporal-developmental change involves change from conceptual to factual orientation, movement from “rear” to “front” of our system of knowledge, and “fixing” and “unfixing” concepts and theories. These dynamics explain the presence of logic and philosophy in the periphery, highlight the model’s flexibility, reconcile the tension between apparently incompatible tenets (e.g., holism and compositionality), account for continuity through change, counter the simplistic view of knowledge as a “mirror representation” of reality, throw light on two important aspects of language—semantic ascent and ontological descent, and in general demonstrate that richness of structure enhances explanatory power.Less
The chapter focuses on the dynamics of the model of knowledge delineated in Chapter 3. Epistemic units move across the model along two axes: context and time. Contextual movement is due to variations in perspective and to a multiplicity of factors concerning both the world and the knower. Temporal-developmental change involves change from conceptual to factual orientation, movement from “rear” to “front” of our system of knowledge, and “fixing” and “unfixing” concepts and theories. These dynamics explain the presence of logic and philosophy in the periphery, highlight the model’s flexibility, reconcile the tension between apparently incompatible tenets (e.g., holism and compositionality), account for continuity through change, counter the simplistic view of knowledge as a “mirror representation” of reality, throw light on two important aspects of language—semantic ascent and ontological descent, and in general demonstrate that richness of structure enhances explanatory power.
