I think the English measurement story is simply one of path dependence. It is entrenched, lots of people know it, and it would cost a lot in infrastructure and learning to switch, just like the QWERTY keyboard. OTOH, the English language has considerable nuance, given the many languages that go into it.
The Pareto distribution argument is in the right direction. Think of a skewed distribution versus a normal one. So, the mean of the normal one might be higher than that of the skewed one. On average it does better, and hence may be more popular. But the skewed one has this tail that does much better than the normal one a non-trivial amount of the time, so that risk lovers are attracted to it. This is not all that different from the argument about how noise traders survive in financial markets. Most go bankrupt, but those who actually did buy low and sell high do better than anybody else in the market and definitely survive.
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knackeredhack,
Forecasting markets in general is a mug's game, only made worse when bubbles go on. Go read all the debates about the (maybe) housing bubble going on over at Econbrowser. There is a deep argument, which Jim Hamilton has long been one of the main promulgators of, that one can never identify for certain econometrically if one is in a bubble or not, although one may be able to do so pretty much for certain sometimes with closed-end funds, where there is a well-defined fundamental in the net asset value of the fund.
Regarding Sornette, his model is one of a rational stochastically crashing bubble, which requires a sharp upward acceleration to provide risk premia for the rising probability of the inevitable crash. These tend to go to infinity at a certain point, which is the basis for forecasting the crash that Sornette uses. Of course there is plenty of reason to believe that people in bubbles are not fully rational, and therefore it is not surprising that Sornette has had a rather mixed record in his forecasting.