Yaneer Bar-Yam and Nassim discuss the COVID-19 situation with some disagreements.
A first, very introductory presentation of fragility as linked to both nonlinearity and dislike of variations. Antifragility is almost the opposite, limited to a specific range of variations.
- Why everything fragile must be concave.
- The medical S curve.
- Why harm to the climate is necessarily nonlinear in dose response.
- How hospitals can be overcrowded unless there are redundancies.
Further discussions will be more technical.
Technical Appendix to the paper on violence: What do you do when the data looks like it is power law distributed over a broad range, but cannot be technically a power law? We use dual distribution and transport parameters between one and another.
Violence is from Extremistan, hence requires some more sophisticated tools since LLN works slowly. We see how Pinker’s thesis is bogus. We look at ways to integrate the factual unreliability of historical accounts. We look at transformations to analyze violence using Power law tools since the worst case is bounded at the contemporary population level.
Links to Papers with Pasquale Cirillo
On the statistical properties and tail risk of violent conflicts [TECHNICAL, PHYSICA A]
The Decline of Violent Conflicts: What Do the Data Really Say? [NONTECHNICAL, NOBEL FOUNDATION]
How to look at the risks of Covid vaccines, why they are much lower than you think. We never had a larger monitored sample size in history and it allows events that on average show up later to manifest themselves very early on. Rationale: It takes a long time in a casino for someone to win 8 times in a row. But if 8 billion people played at the same time you would certainly witness a minimum of such events every day.