Writing
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Beyond 37%: When Optimal Stopping Stops Being Useful
The classical secretary problem gives 1/e ≈ 37%, but the rule answers a question almost no one actually asks. Six simulations covering recall, cardinal payoffs, full information, two-sided choice, learned priors, and a market-timing backtest where the naive no-policy baseline beats every stopping rule.
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Habits, Trust, and the Korean Telemedicine Collapse
Korea's June 2023 telemedicine pilot collapsed take-up to 0.16% of NHIS claims despite eligibility rules that explicitly targeted chronic-disease elderly. Using DML and causal forests on linked claims data, I estimate the behavioral residual on always-eligible, always-supplied patients and trace roughly half its variance to habit strength and patient–provider trust.