The Tipping Point: How Little Things Can - By Gladwell, Malcolm Page 0,103
a way. In a world dominated by isolation and immunity, understanding these principles of word of mouth is more important than ever.
Endnotes
INTRODUCTION
Page 5.
For a good summary of New York City crime statistics, see: Michael Massing, “The Blue Revolution,” in the New York Review of Books, November 19, 1998, pp. 32–34. There is another good discussion of the anomalous nature of the New York crime drop in William Bratton and William Andrews, “What We’ve Learned About Policing,” in City Journal, Spring 1999, p. 25.
Page 10.
The leader in research on yawning is Robert Provine, a psychologist at the University of Maryland. Among his papers on the subject are:
Robert Provine, “Yawning as a Stereotyped Action Pattern and Releasing Stimulus,” Ethology (1983), vol. 72, pp. 109–122.
Robert Provine, “Contagious Yawning and Infant Imitation,” Bulletin of the Psychonomic Society (1989), vol. 27, no. 2, pp. 125–126.
Page 12.
The best way to understand the Tipping Point is to imagine a hypothetical outbreak of the flu. Suppose, for example, that one summer 1,000 tourists come to Manhattan from Canada carrying an untreatable strain of twenty four hour virus. This strain of flu has a 2 percent infection rate, which is to say that one out of every 50 people who come into close contact with someone carrying it catches the bug himself. Let’s say that 50 is also exactly the number of people the average Manhattanite—in the course of riding the subways and mingling with colleagues at work—comes into contact with every day. What we have, then, is a disease in equilibrium. Those 1,000 Canadian tourists pass on the virus to 1,000 new people on the day they arrive. And the next day those 1,000 newly infected people pass on the virus to another 1,000 people, just as the original 1,000 tourists who started the epidemic are returning to health. With those getting sick and those getting well so perfectly in balance, the flu chugs along at a steady but unspectacular clip through the rest of the summer and the fall.
But then comes the Christmas season. The subways and buses get more crowded with tourists and shoppers, and instead of running into an even 50 people a day, the average Manhattanite now has close contact with, say, 55 people a day. All of a sudden, the equilibrium is disrupted. The 1,000 flu carriers now run into 55,000 people a day, and at a 2 percent infection rate, that translates into 1,100 cases the following day. Those 1,100, in turn, are now passing on their virus to 55,000 people as well, so that by day three there are 1,210 Manhattanites with the flu and by day four 1,331 and by the end of the week there are nearly 2,000, and so on up, in an exponential spiral, until Manhattan has a full blown flu epidemic on its hands by Christmas Day. That moment when the average flu carrier went from running into 50 people a day to running into 55 people was the Tipping Point. It was the point at which an ordinary and stable phenomenon—a low level flu outbreak—turned into a public health crisis. If you were to draw a graph of the progress of the Canadian flu epidemic, the Tipping Point would be the point on the graph where the line suddenly turned upward.
Tipping Points are moments of great sensitivity. Changes made right at the Tipping Point can have enormous consequences. Our Canadian flu became an epidemic when the number of New Yorkers running into a flu carrier jumped from 50 to 55 a day. But had that same small change happened in the opposite direction, if the number had dropped from 50 to 45, that change would have pushed the number of flu victims down to 478 within a week, and within a few weeks more at that rate, the Canadian flu would have vanished from Manhattan entirely. Cutting the number exposed from 70 to 65, or 65 to 60 or 60 to 55 would not have been sufficient to end the epidemic. But a change right at the Tipping Point, from 50 to 45, would.
The Tipping Point model has been described in several classic works of sociology. I suggest:
Mark Granovetter, “Threshold Models of Collective Behavior,” American Journal of Sociology (1978), vol. 83, pp. 1420–1443.
Mark Granovetter and R. Soong, “Threshold Models of Diffusion and Collective Behavior,” Journal of Mathematical Sociology (1983), vol. 9, pp. 165–179.
Thomas Schelling, “Dynamic Models of Segregation,” Journal of Mathematical Sociology (1971), vol. 1, pp. 143–186.
Thomas Schelling, Micromotives and Macrobehavior (New York: W. W.