Length and Segmentation in a Limited Verification Queue
Abstract
Verification effort should respond to uncertainty and consequence, yet convenient proxies for risk can be misleading. This article examines the association between response length and any-error labels in FELM using conventional Logit models with domain controls and a sensitivity adjustment for segment count. The main length coefficient is positive; adding segment count widens its interval enough to include zero. That change motivates a careful distinction between an observed risk marker and a causal intervention. The article compares sequential allocation, acceptable-set selection, robust constraints, and adaptive artificial intelligence as ways to organize a verification budget. It proposes an evidence-based evaluation design without claiming to have tested a new allocation algorithm.
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