~/coverage-then-densityWhether a marginal vote should buy a new edge or repeat an old one is not a constant; it is a schedule. In 150-replicate calibrated simulation, single-vote edges dominate below roughly eight votes per item, where every fresh edge adds structure the estimator lacks. Beyond that, redundant votes win: the graph is connected, and precision on existing edges outbids novelty. Global order quality (Kendall tau) still favors coverage late, but payout accuracy favors density, because payouts are dominated by the well-connected top of a heavy-tailed score distribution. The optimal policy starts wide and ends deep.
~/lazy-chainRank centrality's convergence is a property of the chain's laziness, and a scaling choice decides it. Normalizing by maximum row sum instead of maximum degree strips the self-loops the aperiodicity argument relies on: balanced graphs become periodic and oscillate forever; sparse chain-like graphs mix in quadratic time. Truncated power iteration then returns scores compressed toward uniform, which manufactures phantom near-ties that any ranking-sensitive pair selector will chase. A solver artifact can wear an algorithm's costume. Degree scaling and an exact stationary solve remove the costume.
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