Human cycles: History as science
To Peter Turchin, who studies population dynamics at the University of Connecticut in Storrs, the appearance of three peaks of political instability at roughly 50-year intervals is not a coincidence. For the past 15 years, Turchin has been taking the mathematical techniques that once allowed him to track predator–prey cycles in forest ecosystems, and applying them to human history. He has analyzed historical records on economic activity, demographic trends and outbursts of violence in the United States, and has come to the conclusion that a new wave of internal strife is already on its way. The peak should occur in about 2020, he says, and will probably be at least as high as the one in around 1970. “I hope it won't be as bad as 1870,” he adds.But also see an opposing viewpoint from Maria Konnikova,
Humanities aren't a science. Stop treating them like one
Yes, we could say, we can predict this and avert that and explain this and understand that. But you know what? The cliodynamists, just like everyone else, will only know which cyclical predictions were accurate after the fact. Forgotten will be all of those that were totally wrong. And the analysts of myths only wait for the hits to make their point—but how many narratives that are obviously not based in reality have similar patterns?
We’re held back by those biases that plague almost all attempts to quantify the qualitative, selection on the dependent variable and post hoc hypotheses and explanations. We look at instances where the effect exists and posit a cause—and forget all the times the exact same cause led to no visible effect, or to an effect that was altogether different. It’s so easy to tell stories based on models. It’s so hard to remember that they are nothing more than stories. (It’s not just history or literature. Much of fMRI research is blamed for precisely that reason: if you don’t have an a priori hypothesis but then see something interesting, it’s all too tempting to explain its involvement after the fact and pretend that that’s what you’d meant to do all along. But the two approaches are not one and the same.)I particularly like the comparison with fMRI research.