In the nineteenth century scientists began a systematic study of society using tools from the physical sciences. One such tool was statistics and the bell-shaped curve of Gauss. Today students are often graded with the expectation that a certain fraction will have A or F, a larger fraction will have B or D and most students will obtain a grade of C. This expectation is based on the statistics of Gauss, the average value and the notion that life ought to be fair.
We will explore the fallacy behind the reasoning for applying the bell-shaped curve to such complex phenomena as learning/teaching. In fact, I will argue that it is only in the physical sciences that phenomena are sufficiently simple that the statistics of Gauss apply; in the social and life sciences it is the inverse power law of Pareto that describes phenomena. From the distribution of wealth to the beating of the human heart we find that life has a fundamental imbalance, both in the distribution of wealth and in the measures of health.
The presentation will provide data from the life and social sciences so the audience will be able to follow the arguments without the burden of mathematics.
Dr. Bruce J. West received his Ph.D. in Statistical Nonlinear Physics from the University of Rochester in 1970. At present, he is the Chief Scientist of the Mathematical and Information Science Directorate at the US Army Research Office. Previously, he was a research scientist at La Jolla Institute, and for ten years a professor of physics in the University of North Texas. Over the years, his research interest has consistently focus in the application of nonlinear dynamics to biomedical and social phenomena. He has published eight books in these areas over the past twenty years at various levels of mathematical sophistication, founding such research areas as fractal physiology. He has published over 250 research articles; is a Fellow of the Army Research Laboratory; and a Fellow of the American Physical Society. Dr. West most recent work entitled: Where Medicine Went Wrong is the inspiration for his SCTPLS 2007 presentation.
Gell-Mann distinguishes between (1) the traditional regularities of normal science studied by reductionism using equations to formalize law-like algorithmic reductions; and (2) scale-free regularities appearing across multiple levels of “living” systems, which stem from chaotic, tiny initiating events to become frozen accidents. Here, elements of chaos theory and complex adaptive systems (CAS) are combined to highlight a fundamentally different kind of regularity requiring different kinds of scientific methods. Chaos and complexity theories are again joined. Since all living systems are under adaptive pressure, it follows that the second regularity is ubiquitous. Since 1950 species-abundance biologists such as Preston, MacArthur and Holling along with SFI’s Per Bak, a physicist, have suggested lognormal/power law phenomena represent a natural law of efficacious adaptation, ranging from moths to earthquakes and wars. Murray Gell-Mann’s second regularity gives more credence to this idea: (1) a multi-level system must have scalable cas dynamics at multiple levels for adaptive success; and (2) efficaciously adaptive CAS dynamics, and indications of them, should exhibit power law signatures explainable via scale-free theories. There are a growing number of clues suggesting this idea to be correct. We already know this to be true with at least one core feature of human life—the best indicator of impending heart attack and death is a non-fractal heartbeat! Additional and better tests of this idea should be at the top of chaos and complexity researchers’ agendas. If the basis for believing that power laws are indicators of efficacious adaptation strengthens—is proved broadly true—it follows that scale-free, nonlinear dynamics are indeed the core feature of all living systems.
Dr. Bill McKelvey received his Ph.D. from MIT, 1967. He is a Professor of Strategic Organizing and Complexity Science at UCLA's Anderson School. McKelvey's Organizational Systematics book remains a definitive treatment of organizational taxonomy and evolution. He chaired the building committee that produced the $110,000,000 Anderson Complex. He directed over 170 field study teams on strategic improvements to client firms. In 1997 he initiated activities leading to the founding of UCLA's Center for Complex Human Systems & Computational Social Science. McKelvey has co-edited Variations in Organization Science (1999) and special issues of E:CO and JIT. He has 40 publications on complexity science applied to organizations.