Every Tuesday, we discuss tipping points in the TIPPING+ project for the European Commission. The tipping point phenomenon is a sudden change in the current state of the system. The tipping point appears when a system change parameters, causing a massive shift from one stable attractor to another. For example, the corona pandemic causes online education's attractor to become rapidly stronger, and schooling suddenly moves online.
The second way is when the shaking of the current situation becomes so large that it eclipses what makes the system branch out. This means that the swing in the situation causes the state of the system to pass from the boundary of the current stable attractor's area of attraction to another stable attractor's area of attraction. This is also the case, for example, with PTA, which want to promote online education, which creates a movement and leads to online education at once.
As for the actual example of online education, both movements would have been present in the Corona pandemic, and I don't think it is possible to say that only one of them had an impact. The maximum sway that a system's state will remain in its current stable attractor is called resilience.
The study of resilience originally started in biology, with examples of ecosystems that suddenly shifted and couldn't quite get back to their original state, but nowadays, we're thinking of using it for things like climate change and the bursting of financial bubbles. However, we can look back and analyse why tipping points happened in the past and show that similar situations may lead to another tipping point, but we can't predict when it will happen. So it is impossible to predict when the current financial situation, which is called a bubble, will burst. However, there are people who want to study the critical slowdown that precedes the tipping phenomenon to predict it. This paper summarises the methods used to analyse this critical slowdown situation.
If you can't predict when the tipping point will occur, it makes sense to analyse the critical slowdown that precedes it. When do we see the calm before the storm?
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