
Simplifying Complexity: Life is Uncertain, Unfair and Unequal
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In life, we often face unavoidable complexities in terms of our ability to understand or influence outcomes. Some questions which arise due to these complexities are: Why can't the future be made certain? Why do the some people or events always end up at the center of controversy? Why do only a select few get ahead of their peers? Each question pertains to three central elements of complexities and these elements are: uncertainty, inequality and unfairness.
Simplifying Complexity explains the scientific study of complex cognitive networks, as well as the methods scientists use to parse difficult problems into manageable pieces. Readers are introduced to scientific methodology and thought processes, followed by a discourse on perspectives on the three elements of complexity through concepts such as normal and non-normal statistics, scaling and complexity management.
Simplifying Complexity combines basic cognitive science and scientific philosophy for both advanced students (in the fields of sociology, cognitive science, complex networks and change management) and for general readers looking for a more scientific guide to understanding and managing the nature of change in a complex world.
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Content
- Intro
- CONTENTS
- FOREWORD
- PREFACE
- CONFLICT OF INTEREST
- ACKNOWLEDGEMENTS
- PROLOGUE
- How Scientists Think
- 1.1. ONE SCIENTIST'S VIEW
- 1.1.1. Changing Perspective
- 1.1.2. Grand Visions
- 1.2. POPULATION MODELS AND QUANTITATIVE REASONING
- 1.2.1. Exponential Growth
- 1.2.2. Saturation
- 1.2.3. Chaos
- 1.3. SOCIOTECHNOLOGY GROWTH AND MEASURED THOUGHT
- 1.3.1. Evolution as Replacement
- 1.3.2. Multiple Saturations
- 1.4. ASSESSMENT
- Uncertain: A Simple World View
- 2.1. NORMALCY
- 2.1.1. Examples
- 2.1.2. Drunkard's Walk
- 2.2. THE IMPORTANCE OF LINEARITY
- 2.2.1. Additive
- 2.2.2. Independent
- 2.2.3. Practical
- 2.3. THE NORMAL VIEW IS STRENGTHENED
- 2.3.1. Sociophysics
- 2.3.2. Psychophysics
- 2.3.3. Medicine
- 2.4. LINEAR AND RANDOM
- 2.4.1. Evolutionary Science
- 2.4.2. Inferences
- 2.4.3. Handicapping
- 2.5. STATISTICS, SPECTRA AND SCALING
- 2.5.1. Oil Spill
- 2.5.2. Normal Modeling
- 2.6. REASSESSMENT
- Unfair: A Complex World View
- 3.1. THE IMBALANCE
- 3.1.1. Non-Normal Grades
- 3.2. NON-NORMAL STATISTICS
- 3.2.1. Quake Sizes
- 3.2.2. Quake Times
- 3.2.3. Power Grids
- 3.3. FLASH CRASHES IN HEALTH CARE
- 3.3.1. Hospitals
- 3.3.2. Bursts
- 3.4. VIEWS OF COMPLEXITY
- 3.4.1. Prey-Predator System
- 3.4.2. Generalizing Random Walks
- 3.4.3. Nonlinear Dynamics
- 3.4.4. Fractals
- 3.4.5. Fractal Dimension
- 3.5. THE TYRANNY OF EXTREMES
- 3.5.1. Tipping Points
- 3.5.2. Simple Extrema
- 3.5.3. Complex Extrema
- 3.6. HOW UNFAIR IS IT?
- Unequal: A Matter of Scale
- 4.1. CRITICALITY AND MULTIPLE SCALES
- 4.1.1. Time
- 4.1.2. Space
- 4.1.3. Decision Making Model
- 4.1.4. Frequency
- 4.2. SCALING MECHANISMS
- 4.2.1. Hierarchical Effect
- 4.2.2. Entrepreneurial Effect
- 4.2.3. Allometry Effect
- 4.2.4. Gambler's Ruin Effect
- 4.2.5. Matthew Effect
- 4.2.6. Modulated Fluctuations Effect
- 4.2.7. Contagion Effect
- 4.2.8. Criticality Effect
- 4.2.9. Maximum Entropy Effect
- 4.3. RANK ORDER
- 4.4. WHY INVERSE POWER LAWS?
- Complexity Management Principle
- 5.1. UNIVERSAL LAWS AND PRINCIPLES
- 5.1.1. Measures of Influence
- 5.1.2. New Principle
- 5.2. APPLICATIONS OF THE NEW PRINCIPLE
- 5.2.1. Habituation
- 5.2.2. Leaky Faucets and Classical Music
- 5.2.3. Global Warming
- 5.3. PINK (1/F) NOISE
- 5.3.1. Memory
- 5.3.2. Decision Making
- 5.4. NETWORK-CENTRIC WARFARE
- 5.5. WRAP-UP
- Apology for Complexity
- 6.1. SUMMARY OF CHAPTERS
- 6.2. THE INDIVIDUAL AND THE ORGANIZATION
- 6.3. A FINAL WORD
- 6.4. EPILOGUE
- References
- SUBJECT INDEX
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The file format ePUB works well for novels and non-fiction books – i.e., 'flowing' text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook does not use copy protection or Digital Rights Management
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