There is a quiet scandal in applied mathematics: the machinery does not know what it is being pointed at. A Markov chain is a set of states and a matrix of probabilities for moving between them. It is supremely indifferent to whether those states are weather, a stock, a molecule, or a community losing the confidence it runs on.
The same transition matrix that estimates where a price lands tomorrow will, unchanged, describe how trust migrates between institutions. Estimate the probabilities from history, roll them forward, and read the stationary distribution — the long-run state the system forgets its way into regardless of where it started.
The lesson for sovereign thinking is not the mush that “everything is connected.” It is sharper: a small number of structural ideas recur across wildly different domains, and owning one outright is worth more than a thousand borrowed conclusions. Below, the matrix is yours to perturb — nudge a probability and watch the whole future migrate.