Melting Point: Gladwell’s Tipping Point in Climate Science

By Rachel Newstadt

The idea of a “tipping point,” as explained by Malcolm Gladwell, is a relatively simple one: change in a system builds slowly, then reaches a certain level, the tipping point, and change is then sudden and dramatic. He further explains his theory with characteristics of these tipping points, which include: there are a certain few who can have disproportionate impacts on the change, and the context in which the change is happening matters. This idea is an elaboration of a type of gradual change explained by Paul Pierson: threshold effects, in which forces generate incremental changes until reaching a critical level, triggering “major changes” (Pierson 86).

An example of a process that is argued to have a tipping point is climate change: as the earth warms, it will reach certain tipping points, and going over these thresholds of global temperature will lead to massive changes in the world as we know it. A number of authors have argued that tipping points are clear throughout environmental science, but a particularly relevant study was one done by Tim Lenton of the University of Exeter, discussing ice melt and sea level rise. Lenton discusses the role that the melting of various ice sheets will impact the future, leading to more melting ice, and, eventually a tipping point, beyond which the entire ice sheet will be forever lost, significantly raising sea levels. A few ice sheets he examines (the Arctic, and Greenland ice sheets, the Yedoma Permafrost) are examples of the “certain few” with a disproportionate impact referred to by Gladwell. Additionally, the context -- other contributors to sea melt (ozone holes, etc) -- will contribute to these changes. Climate science is incredibly complicated, but ice melt and sea level rise is a clear example of an aspect of this science with a tipping point. 

Gabon: Nunn’s Unexplained Outlier

By Rachel Newstadt

In Nathan Nunn’s article, he argues that slavery and the violence the system depended upon led to increased fractionalization, which led to weaker state-building institutions and eventually to decreased income (Ibid). For the most part, this seems to hold true. In the results of Nunn’s regression analysis, it is clear that most states fall along the line of best fit. However, there are a few notable exceptions, including Gabon. In terms of slave exports, Gabon falls in the center of the global distribution, exporting approximately the same amount of slaves per capita as the Ivory Coast or Cameroon; yet Gabon’s GDP is far better than either of these countries (Nunn 153). All three countries are, upon first glance, fairly similar. Nunn neglects to explain why his theory fails in this instance, mentioning Gabon only to claim that there were fewer exports per capita in Gabon because society there was violent and hostile to the Portuguese traders (Nunn 158).

Gabon does fit into Nunn’s other claim that states that were weaker prior to the arrival of slavers were systematically less likely to be a main source for slaves. However, this claim by Nunn is based on uncontested and relatively weak evidence that population density is a good measure of economic prosperity (Nunn 158). Gabon's exception is further compounded when examining the rest of Nunn’s paper. Nunn further claims that factors contributing to the impacts of slavery included endogenous factors to these states. Ethnic fractionalization was an important determining factor for future economic growth (Nunn 165). Gabon, however, has a relatively high level of ethnic fractionalization. The population includes “40 or so peoples” and the ethnic fractionalization, measured by ELF, is relatively high at 0.69.

While Nunn’s theory is overall strong, certain points are uncertain, and outliers such as the state of Gabon are left totally unexplained.